diff --git a/blog/2/index.html b/blog/2/index.html index 51f3d9a8..38c08429 100644 --- a/blog/2/index.html +++ b/blog/2/index.html @@ -52,4 +52,4 @@ } } }) -
Konveyor is now a Cloud Native Computing Foundation (CNCF) Sandbox project

Konveyor Blog

Jun 16, 2022

Tackle 2: New capabilities for modernizing applications to leverage Kubernetes

New management, assessment, and analysis capabilities will help you streamline the modernization of your application portfolio to Kubernetes. See what is new with the open source tool Tackle 2.0.

Mar 9, 2022

Application Modernization Report Shows Need For Kubernetes-specific Migration Tooling

In MTC 1.4.0, a new feature called Direct Migration is available that will yield significant time savings for most customers migrating persistent volumes and/or internal images.

Dec 21, 2021

Konveyor Community HackFest

Get free hands-on experience migrating different workload types to Kubernetes with open source tools and community engineer support.

Mar 3, 2021

Exploring a Metrics-Driven Approach to Transformation

When we started providing professional services around enterprise Kubernetes, it became clear we needed a program-level framework for adopting containers that spelled out the activities of multiple project teams.

Feb 24, 2021

Migrating Faster with Direct Migration

In MTC 1.4.0, a new feature called Direct Migration is available that will yield significant time savings for most customers migrating persistent volumes and/or internal images.

\ No newline at end of file +
Konveyor is now a Cloud Native Computing Foundation (CNCF) Sandbox project

Konveyor Blog

Jul 7, 2022

A Method to Measure and Manage Technical Debt

we demonstrate that not only is technical debt key to making decisions regarding any specific application, it is also important when attempting to prioritize work between multiple applications.

Jun 16, 2022

Tackle 2: New capabilities for modernizing applications to leverage Kubernetes

New management, assessment, and analysis capabilities will help you streamline the modernization of your application portfolio to Kubernetes. See what is new with the open source tool Tackle 2.0.

Mar 9, 2022

Application Modernization Report Shows Need For Kubernetes-specific Migration Tooling

In MTC 1.4.0, a new feature called Direct Migration is available that will yield significant time savings for most customers migrating persistent volumes and/or internal images.

Dec 21, 2021

Konveyor Community HackFest

Get free hands-on experience migrating different workload types to Kubernetes with open source tools and community engineer support.

Mar 3, 2021

Exploring a Metrics-Driven Approach to Transformation

When we started providing professional services around enterprise Kubernetes, it became clear we needed a program-level framework for adopting containers that spelled out the activities of multiple project teams.

Feb 24, 2021

Migrating Faster with Direct Migration

In MTC 1.4.0, a new feature called Direct Migration is available that will yield significant time savings for most customers migrating persistent volumes and/or internal images.

\ No newline at end of file diff --git a/blog/application-modernization-report/index.html b/blog/application-modernization-report/index.html index 57e45775..17d0c7a9 100644 --- a/blog/application-modernization-report/index.html +++ b/blog/application-modernization-report/index.html @@ -53,4 +53,4 @@ } })
Konveyor is now a Cloud Native Computing Foundation (CNCF) Sandbox project

Mar 9, 2022

Application Modernization Report Shows Need For Kubernetes-specific Migration Tooling

Tags:

Konveyor is a community of people passionate about helping others modernize and migrate their applications to the hybrid cloud by building tools, identifying patterns, and providing advice on how to break down monoliths, adopt containers, and embrace Kubernetes. To do so the Konveyor community is currently working on five projects to help users rehost, replatform, and refactor their applications to Kubernetes.

While conversations with users and data from various sources gave us some visibility into how migrations were taking place, we wanted to inform our priorities with recent detailed data. To do so, Red Hat, a Konveyor community contributor, sponsored a survey of 600 IT decision makers, backend developers, and software architects in the US, UK, and English-speaking Asia-Pacific (APAC) to better understand the application modernization landscape.

Here are some of the findings that relate to Konveyor and application modernization:

Application modernization is happening now

It’s clear that there is urgency to roll out migration tooling. Among those we surveyed, those who were migrating or planning to, we found that they plan to modernize over half of their custom applications during the next year and over a quarter during the next six months. Only 20% expected the modernization to take more than two years. It’s clear this is happening right now.

That said, it’s not all smooth sailing and this doesn’t happen overnight. While some regions haven’t progressed far enough in their application modernization journey to experience serious barriers, others (notably the US) report that choosing a straightforward approach can be challenging. Organizations have many options to choose from and each option presents varying levels of complexity.

Companies plan for more than half of their custom applications to be modernized within the next year.

Motivators for modernizing existing applications to Kubernetes

The survey tells us modernization is mostly being driven by the need for reliability, scalability and security. Decreasing costs were also on the list but, as we frequently see in other surveys about technology adoption or change, it’s not the driving factor.

Most companies decide to modernize their applications to increase scalability or reliability. Companies in APAC also seek to improve security and customer experience, while those in the US and UK want to decrease costs.

Konveyor’s tool suite can be used to help realize organization’s migration plans.

How migration strategies companies intend to use based on this survey map to the Konveyor Tool Suite.

The Konveyor tool suite maps closely to the migration strategies companies intend to use based on this survey: rehosting, replatforming, and refactoring.

Companies intend to replatform, refactor, or repurchase just over half of their custom legacy applications.

Rehost applications to cloud with Forklift and Crane

Rehosting (20% of total) involves copying applications to a cloud (whether hosted or on-prem) with minimal changes, i.e. “lift and shift.” This will be familiar to anyone with experience in virtualization early on when bare metal servers were often moved to a virtual machine (VM) for greater efficiency but with little or no changes to the software and with relatively modest operational changes.

While rehosting doesn’t provide the same depth of benefits as replatforming or refactoring, it’s the first step in the right direction. Rehosting was the single most common approach -Forklift and Crane are the relevant Konveyor projects here. Forklift is focused on migrating VMs to Kubernetes and provides the ability to migrate multiple VMs to KubeVirt with minimal downtime.

Crane is a rehosting tool that meets a different use case. Crane helps organizations to migrate applications between Kubernetes clusters. There are many times when developers and operations teams want to migrate between older and newer versions of Kubernetes, evacuate a cluster, or migrate to different underlying infrastructure.

Replatforming applications with Move2Kube

Replatforming (18% of total) is using a cloud migration to upgrade operating systems, databases, and other components as needed in order to cloud-enable applications without changing core application code or architecture. Think of it as “lift, tinker, and shift.”

This is effectively an intermediate step between just rehosting and refactoring. In fact, it’s often a stepping stone; the survey found that 90% of those planning to refactor their apps plan to replatform them first.

Move2Kube is a Konveyor project that allows customers to replatform their applications to Kubernetes orchestrated platforms. One area where replatforming is taking place is in the consolidation of container orchestration platforms to Kubernetes.

Due to this consolidation, the Move2Kube project was started to focus on accelerating the process of replatforming to Kubernetes from platforms such as Swarm and Cloud Foundry. This project translates existing artifacts to Kubernetes artifacts to speed up the process of being able to run applications on Kubernetes.

Refactoring applications with Tackle

Refactoring (17%) is often viewed as the most challenging application modernization strategy but it’s the one with the most long-term impact. Refactoring involves re-architecting as cloud-native, for example, by containerizing workloads, transforming a monolith to microservices, or moving functions to a serverless architecture.

While Tackle is not a full refactoring tool, it provides a series of interrelated tools that allow users to assess, analyze, and ultimately move their applications onto a Kubernetes orchestrated platform.

    As you can see, organizations are taking a thoughtful approach to app migration and there’s no single right path. This data supports the Konveyor community’s approach of providing a toolbox, rather than just a singular tool, that can support transitioning applications however it is happening.

    \ No newline at end of file +Forklift and Crane are the relevant Konveyor projects here. Forklift is focused on migrating VMs to Kubernetes and provides the ability to migrate multiple VMs to KubeVirt with minimal downtime.

    Crane is a rehosting tool that meets a different use case. Crane helps organizations to migrate applications between Kubernetes clusters. There are many times when developers and operations teams want to migrate between older and newer versions of Kubernetes, evacuate a cluster, or migrate to different underlying infrastructure.

    Replatforming applications with Move2Kube

    Replatforming (18% of total) is using a cloud migration to upgrade operating systems, databases, and other components as needed in order to cloud-enable applications without changing core application code or architecture. Think of it as “lift, tinker, and shift.”

    This is effectively an intermediate step between just rehosting and refactoring. In fact, it’s often a stepping stone; the survey found that 90% of those planning to refactor their apps plan to replatform them first.

    Move2Kube is a Konveyor project that allows customers to replatform their applications to Kubernetes orchestrated platforms. One area where replatforming is taking place is in the consolidation of container orchestration platforms to Kubernetes.

    Due to this consolidation, the Move2Kube project was started to focus on accelerating the process of replatforming to Kubernetes from platforms such as Swarm and Cloud Foundry. This project translates existing artifacts to Kubernetes artifacts to speed up the process of being able to run applications on Kubernetes.

    Refactoring applications with Tackle

    Refactoring (17%) is often viewed as the most challenging application modernization strategy but it’s the one with the most long-term impact. Refactoring involves re-architecting as cloud-native, for example, by containerizing workloads, transforming a monolith to microservices, or moving functions to a serverless architecture.

    While Tackle is not a full refactoring tool, it provides a series of interrelated tools that allow users to assess, analyze, and ultimately move their applications onto a Kubernetes orchestrated platform.

      As you can see, organizations are taking a thoughtful approach to app migration and there’s no single right path. This data supports the Konveyor community’s approach of providing a toolbox, rather than just a singular tool, that can support transitioning applications however it is happening.

      \ No newline at end of file diff --git a/blog/community-update-konveyor-refocuses-efforts/index.html b/blog/community-update-konveyor-refocuses-efforts/index.html index e49bf447..a5dee291 100644 --- a/blog/community-update-konveyor-refocuses-efforts/index.html +++ b/blog/community-update-konveyor-refocuses-efforts/index.html @@ -52,4 +52,4 @@ } } }) -
      Konveyor is now a Cloud Native Computing Foundation (CNCF) Sandbox project

      Oct 20, 2022

      Community Update: Konveyor Refocuses Efforts on Replatforming and Refactoring Use Cases

      Tags:

      In the latest community update, we revealed upcoming changes to the Konveyor Project. These adjustments are designed to solve the most important application modernizations problem better and to encourage participation with our community. Here’s what we announced:

      • We will solely focus on solving for the replatforming and refactoring use cases.
      • It’s easier to contribute and collaborate with Konveyor thanks to our new special interest group (SIG) model.
      • You can learn the Konveyor project, see upcoming features, and give us feedback at our workshop — part of the OpenShift Commons Gathering at KubeCon NA 2022. Register for the Gathering to secure your spot.
      • Tackle 2.1 is available, future Tackle releases will be branded Konveyor.
      • Konveyor roadmap includes migration wave management, multi language support, and integrations with modernization tools.

      You can get the details of each announcement below.

      We are refocusing efforts on replatforming and refactoring use cases

      A key insight the State of Application Modernization Report surfaced is that users are more interested in replatforming and refactoring then just rehosting workloads or “lifting and shifting”. Paired with feedback from users, this revealed a gap in the tooling for refactoring which Konveyor is now addressing

      Originally, Konveyor took a “big tent” approach to rehosting, replatforming and refactoring. We brought the tooling to a community of engineers, developers, and users to figure out what problems they need to solve. Now, due to their feedback, Konveyor is refocusing on just replatforming and refactoring, meaning:

      • Pelorus, Tackle and Move2Kube will be integrated and moved into a single project, now called Konveyor.
      • Crane (rehosting from one Kubernetes cluster to another) will be moved into a separate GitHub organization.
      • Forklift (rehosting to VMs) will move into a KubeVirt project focused on running VM’s with Kubernetes.

      Crane and Forklift will continue to exist but will no longer be part of the core Konveyor toolset.

      Project changes: chart showing what will happen to each of the subprojects after the refocus.

      Special interest group (SIG) model makes it easier to contribute and collaborate with the project

      One of the major changes to the Konveyor project is the refocusing on the major areas of code, UI, analyzers, and add-ons, each of which is represented by a special interest group (SIG) modeled after the SIGs created by the Kubernetes community. These groups are responsible for the development, integration, maintenance, and collaboration of the project.

      The SIG Core is responsible for all of the core features of the Konveyor platform. These features include but are not limited to modernization, report generation, integration of program management tools, and the design of implementation of the hub itself.

      SIG UI is responsible for the user interface and experience across the platform. This SIG is also responsible for creating a pattern where all of the add-ons can be dynamically integrated into the hub.

      The SIG Analyzers are working on creating an extensible pattern and standardization of input and output for the community to collaborate on the analyzers. The analyzers will each target specific programming languages.

      Finally SIG Add-ons are responsible for the development and integration of add-ons that will enhance Konveyor’s capabilities.

      The community meetings bring together contributors and collaborators to provide a forum to discuss topics and new ideas and generate innovation, and happen on every first and third Thursday at 9 AM ET (meetings are recorded). Topics include milestones and features of upcoming releases, contributor showcases with member feedback. Above all, these meetings are intended to foster the community around Konveyor.

      There are also many asynchronous opportunities to communicate and collaborate around Konveyor.

      • There is a #konveyor channel on the Kubernetes Slack channel. You can use it to ask any question about the project.
      • Contributors can subscribe to the Konveyor-community email list for community meeting invites and discussions to influence the direction of the community.
      • To get general updates, you can subscribe to the email list.
      • Or for more information, look at the Konveyor community repo — it includes information around governance documents, contributor letter, Get Started Guide, meeting agendas and developer notes.

      Attend the Konveyor workshop at KubeCon North America 2022

      We will run a workshop in the OpenShift Commons Gathering on 25 October, 2022. At this free, hands-on workshop, workshop leaders will take you through an assesment and analysis of a sample application using the Konveyor platform, followed by discussion of the Konveyor Roadmap and Q&A. Whether you are starting or continuing your application modernization journey, this is a great opportunity to learn how to contribute, or just how to use the tools. If you have any questions or just want to connect with the community or workshop, please reach out to Savita Raghunathan at sraghuna@redhat.com or on Slack.

      How to register:

      • Visit registration site and follow the directions below
      • Click “register”
      • Select “Konveyor workshop”
      • Click “continue”
      • Provide your info and submit

      Tackle 2.1 is available, future Tackle releases will be branded Konveyor

      Tackle 2.1 is available, with the ability to upgrade your current Tackle 2.0. Tackle 2.1 will be the final Tackle release. Future releases will bear the name Konveyor, and will begin with version 3.

      The release of Konveyor 3 is envisioned for Q1 2023 pending the restructuring of the architecture, and some specific components to make contribution easier. For some of the more visionary components of Konveyor 4, the goal is to have these features ready for release in 2H 2023.

      In Tackle 2.1 there are several important features:

      Integration with DiVA (Data intensive Validity Advisor), which is now seamlessly integrated with Tackle: everything is available in the domain user interface to enable the new analysis mode. A transcription report tab is now included in analysis reports with detail on the data layer of your applications.

      The next important feature is the ability to bulk delete applications. Before 2.1 it was possible to import applications in bulk, but not delete them. It will also include automated creation of missing entities on CSV import.

      New rules will be included in the next patch to 2.1.1, allowing new migration paths for open JDK 11 to 17 rules, and with Microsoft as a new major player in the Konveyor community, migration to EAP and Spring Boot applications on top of Azure App Service is supported.

      Finally, the Konveyor community did a ton of bug fixing and optimization making this release much more stable than Tackle 2.0.

      Konveyor roadmap

      Diagram showing Konveyor roadmap for the next year

      Looking forward to next year, several important features are visualized for the first release of Konveyor 3. First of these is Migration Waves Management. No one does a “big bang migration” when dealing with thousands of applications, but rather distributes application portfolio modernization across multiple waves. This new feature offers an assisted method for managing these waves, integrated into the main Konveyor user interface.

      Full integration with Tackle Test Generator and Tackle Container Advisor in the main user interface is envisioned for this release as well. With Tackle Test Generator, tests for an application can be stored in your Git repository with a single click.

      Tackle Container Advisor will leverage its’ entity standardization capability using the natural language description of the technology stack of the application, making it easier to ingest data at scale, simplifying CSV imports and Excel importing, and eliminating the need to code the technology stack as a series of separate tasks

      Integration with Jira will allow the user to track and manage the whole migration process. Tackle will allow delegation of implementation to external issue managers or task managers. By creating issues in Jira related to the applications within the portfolio, a project leader can then assign them to developers to perform changes in the application portfolio.

      Custom Migration Targets will be improved by abstracting users away from the complexities of having to assign custom rules without having to deal with these custom rules directly. Information and status on this feature should be available soon.

      Custom rule upload to repositories will be integrated going forward to allow these rules to be uploaded automatically, and to be retrieved to and from source code repositories.

      Tag management will also be improved, with numerous tags assigned to applications it is difficult for the UI to scale this information or consume it. This feature will help make these tags easier to consume.

      Looking even further into the future, Konveyor 4 will bring a whole new set of advanced features including multi language support for analysis, manifest generation and enhanced assessment module.

      Every time Konveyor has been presented to an organization, invariably there is a request for multi language support. In an early prototype the Konveyor community has demonstrated the ability to use language server technology from Microsoft, decoupling the analysis from data models supporting analysis results. It’s very possible that this feature will be ready to ship with Konveyor 4 in May.

      Manifest generation is another important feature: once you’ve successfully adapted source code to run on containers, this will then install the manifest on Kubernetes.

      Finally, feedback on the current Assessment Module is that it’s too opinionated, so the goal is to make it more intelligent and flexible.

      Altogether, the Konveyor Project has undergone a major transformation improving and simplifying, and creating new and better opportunities for building a community around Application Modernization centered around replatforming and refactoring.

      \ No newline at end of file +
      Konveyor is now a Cloud Native Computing Foundation (CNCF) Sandbox project

      Oct 20, 2022

      Community Update: Konveyor Refocuses Efforts on Replatforming and Refactoring Use Cases

      Tags:

      In the latest community update, we revealed upcoming changes to the Konveyor Project. These adjustments are designed to solve the most important application modernizations problem better and to encourage participation with our community. Here’s what we announced:

      • We will solely focus on solving for the replatforming and refactoring use cases.
      • It’s easier to contribute and collaborate with Konveyor thanks to our new special interest group (SIG) model.
      • You can learn the Konveyor project, see upcoming features, and give us feedback at our workshop — part of the OpenShift Commons Gathering at KubeCon NA 2022. Register for the Gathering to secure your spot.
      • Tackle 2.1 is available, future Tackle releases will be branded Konveyor.
      • Konveyor roadmap includes migration wave management, multi language support, and integrations with modernization tools.

      You can get the details of each announcement below.

      We are refocusing efforts on replatforming and refactoring use cases

      A key insight the State of Application Modernization Report surfaced is that users are more interested in replatforming and refactoring then just rehosting workloads or “lifting and shifting”. Paired with feedback from users, this revealed a gap in the tooling for refactoring which Konveyor is now addressing

      Originally, Konveyor took a “big tent” approach to rehosting, replatforming and refactoring. We brought the tooling to a community of engineers, developers, and users to figure out what problems they need to solve. Now, due to their feedback, Konveyor is refocusing on just replatforming and refactoring, meaning:

      • Pelorus, Tackle and Move2Kube will be integrated and moved into a single project, now called Konveyor.
      • Crane (rehosting from one Kubernetes cluster to another) will be moved into a separate GitHub organization.
      • Forklift (rehosting to VMs) will move into a KubeVirt project focused on running VM’s with Kubernetes.

      Crane and Forklift will continue to exist but will no longer be part of the core Konveyor toolset.

      Project changes: chart showing what will happen to each of the subprojects after the refocus.

      Special interest group (SIG) model makes it easier to contribute and collaborate with the project

      One of the major changes to the Konveyor project is the refocusing on the major areas of code, UI, analyzers, and add-ons, each of which is represented by a special interest group (SIG) modeled after the SIGs created by the Kubernetes community. These groups are responsible for the development, integration, maintenance, and collaboration of the project.

      The SIG Core is responsible for all of the core features of the Konveyor platform. These features include but are not limited to modernization, report generation, integration of program management tools, and the design of implementation of the hub itself.

      SIG UI is responsible for the user interface and experience across the platform. This SIG is also responsible for creating a pattern where all of the add-ons can be dynamically integrated into the hub.

      The SIG Analyzers are working on creating an extensible pattern and standardization of input and output for the community to collaborate on the analyzers. The analyzers will each target specific programming languages.

      Finally SIG Add-ons are responsible for the development and integration of add-ons that will enhance Konveyor’s capabilities.

      The community meetings bring together contributors and collaborators to provide a forum to discuss topics and new ideas and generate innovation, and happen on every first and third Thursday at 9 AM ET (meetings are recorded). Topics include milestones and features of upcoming releases, contributor showcases with member feedback. Above all, these meetings are intended to foster the community around Konveyor.

      There are also many asynchronous opportunities to communicate and collaborate around Konveyor.

      • There is a #konveyor channel on the Kubernetes Slack channel. You can use it to ask any question about the project.
      • Contributors can subscribe to the Konveyor-community email list for community meeting invites and discussions to influence the direction of the community.
      • To get general updates, you can subscribe to the email list.
      • Or for more information, look at the Konveyor community repo — it includes information around governance documents, contributor letter, Get Started Guide, meeting agendas and developer notes.

      Attend the Konveyor workshop at KubeCon North America 2022

      We will run a workshop in the OpenShift Commons Gathering on 25 October, 2022. At this free, hands-on workshop, workshop leaders will take you through an assesment and analysis of a sample application using the Konveyor platform, followed by discussion of the Konveyor Roadmap and Q&A. Whether you are starting or continuing your application modernization journey, this is a great opportunity to learn how to contribute, or just how to use the tools. If you have any questions or just want to connect with the community or workshop, please reach out to Savita Raghunathan at sraghuna@redhat.com or on Slack.

      How to register:

      • Visit registration site and follow the directions below
      • Click “register”
      • Select “Konveyor workshop”
      • Click “continue”
      • Provide your info and submit

      Tackle 2.1 is available, future Tackle releases will be branded Konveyor

      Tackle 2.1 is available, with the ability to upgrade your current Tackle 2.0. Tackle 2.1 will be the final Tackle release. Future releases will bear the name Konveyor, and will begin with version 3.

      The release of Konveyor 3 is envisioned for Q1 2023 pending the restructuring of the architecture, and some specific components to make contribution easier. For some of the more visionary components of Konveyor 4, the goal is to have these features ready for release in 2H 2023.

      In Tackle 2.1 there are several important features:

      Integration with DiVA (Data intensive Validity Advisor), which is now seamlessly integrated with Tackle: everything is available in the domain user interface to enable the new analysis mode. A transcription report tab is now included in analysis reports with detail on the data layer of your applications.

      The next important feature is the ability to bulk delete applications. Before 2.1 it was possible to import applications in bulk, but not delete them. It will also include automated creation of missing entities on CSV import.

      New rules will be included in the next patch to 2.1.1, allowing new migration paths for open JDK 11 to 17 rules, and with Microsoft as a new major player in the Konveyor community, migration to EAP and Spring Boot applications on top of Azure App Service is supported.

      Finally, the Konveyor community did a ton of bug fixing and optimization making this release much more stable than Tackle 2.0.

      Konveyor roadmap

      Diagram showing Konveyor roadmap for the next year

      Looking forward to next year, several important features are visualized for the first release of Konveyor 3. First of these is Migration Waves Management. No one does a “big bang migration” when dealing with thousands of applications, but rather distributes application portfolio modernization across multiple waves. This new feature offers an assisted method for managing these waves, integrated into the main Konveyor user interface.

      Full integration with Tackle Test Generator and Tackle Container Advisor in the main user interface is envisioned for this release as well. With Tackle Test Generator, tests for an application can be stored in your Git repository with a single click.

      Tackle Container Advisor will leverage its’ entity standardization capability using the natural language description of the technology stack of the application, making it easier to ingest data at scale, simplifying CSV imports and Excel importing, and eliminating the need to code the technology stack as a series of separate tasks

      Integration with Jira will allow the user to track and manage the whole migration process. Tackle will allow delegation of implementation to external issue managers or task managers. By creating issues in Jira related to the applications within the portfolio, a project leader can then assign them to developers to perform changes in the application portfolio.

      Custom Migration Targets will be improved by abstracting users away from the complexities of having to assign custom rules without having to deal with these custom rules directly. Information and status on this feature should be available soon.

      Custom rule upload to repositories will be integrated going forward to allow these rules to be uploaded automatically, and to be retrieved to and from source code repositories.

      Tag management will also be improved, with numerous tags assigned to applications it is difficult for the UI to scale this information or consume it. This feature will help make these tags easier to consume.

      Looking even further into the future, Konveyor 4 will bring a whole new set of advanced features including multi language support for analysis, manifest generation and enhanced assessment module.

      Every time Konveyor has been presented to an organization, invariably there is a request for multi language support. In an early prototype the Konveyor community has demonstrated the ability to use language server technology from Microsoft, decoupling the analysis from data models supporting analysis results. It’s very possible that this feature will be ready to ship with Konveyor 4 in May.

      Manifest generation is another important feature: once you’ve successfully adapted source code to run on containers, this will then install the manifest on Kubernetes.

      Finally, feedback on the current Assessment Module is that it’s too opinionated, so the goal is to make it more intelligent and flexible.

      Altogether, the Konveyor Project has undergone a major transformation improving and simplifying, and creating new and better opportunities for building a community around Application Modernization centered around replatforming and refactoring.

      \ No newline at end of file diff --git a/blog/direct-migration/index.html b/blog/direct-migration/index.html index 43e794a9..ba4988a6 100644 --- a/blog/direct-migration/index.html +++ b/blog/direct-migration/index.html @@ -79,4 +79,4 @@ MTC orchestrating a direct migration -

      The above diagram shows how MTC orchestrates a direct volume migration by standing up a set of rsync and stunnel pods to directly migrate the PV data from the source to the destination cluster.

      Conclusion

      In MTC 1.4.0, users can expect significant performance enhancements when direct migration is taken advantage of. The direct migration feature also grants the user more granular progress and error reporting back in the user interface to make it easier to debug what went wrong with the migration.

      \ No newline at end of file +

      The above diagram shows how MTC orchestrates a direct volume migration by standing up a set of rsync and stunnel pods to directly migrate the PV data from the source to the destination cluster.

      Conclusion

      In MTC 1.4.0, users can expect significant performance enhancements when direct migration is taken advantage of. The direct migration feature also grants the user more granular progress and error reporting back in the user interface to make it easier to debug what went wrong with the migration.

      \ No newline at end of file diff --git a/blog/index-privacy/index.html b/blog/index-privacy/index.html index 99ac62ec..3494f814 100644 --- a/blog/index-privacy/index.html +++ b/blog/index-privacy/index.html @@ -52,4 +52,4 @@ } } }) -
      Konveyor is now a Cloud Native Computing Foundation (CNCF) Sandbox project

      Privacy Statement for the Konveyor Community

      Scope of This Notice

      This Privacy Statement is intended to describe the Konveyor Project’s privacy practices and provide information about the choices you have regarding the ways in which information collected by the Konveyor Project is used and disclosed. For convenience, the Konveyor Project is referred to in this document as “Konveyor”.

      Our Commitment to Privacy

      At Konveyor, your privacy is important to us. To better protect your privacy, we have provided this Statement explaining our information practices and the choices you can make about the way your personal information is collected, used and disclosed. To make this Statement easy to find, we have made it available on our homepage and at every location where personally-identifiable information may be requested.

      The Information We Collect

      This Privacy Statement applies to all information collected by or submitted to Konveyor, including personal data. “Personal data” is data that can be used to identify an individual.

      Konveyor collects personal data when:

      • you create a Gerrit and/or Bugzilla user account
      • you participate in surveys and evaluations
      • you submit questions or comments to us

      Konveyor may also collect personal data from individuals (with their consent) at conventions, trade shows and expositions.

      The types of personal data collected may include (but are not limited to):

      • your first and last name
      • your title and your company’s name
      • your e-mail address
      • any other identifier that permits Konveyor to make physical or online contact with you
      • any information that Konveyor collects online from you and maintains in association with your account, such as:
        • your GPG key ID
        • your SSH public key
        • your IRC nickname
        • your language preference
        • your timezone

      Publicly Available Personal Data

      In keeping with the open nature and spirit of Konveyor, some personal data attached to Konveyor accounts is made public by default. Specifically:

      • your first and last name
      • your email address
      • your language preference
      • your SSH public key
      • your timezone
      • your GPG key ID (if defined)
      • your IRC nickname (if defined)

      If you wish for this information to be kept private, you can opt-out of displaying this information publicly in your gerrit account preferences. If you choose to opt-out, Konveyor will still have access to this information, but it will not be displayed based on Gerrit capabilities to others, and will be considered Private. The only exception to this is for your email address, which may still be visible in some Konveyor services such as Bugzilla.

      Using (Processing) Your Personal Data Konveyor uses the personal data you provide to:

      • create and maintain your accounts
      • attribute data and content you produce directly and indirectly in our public-facing services
      • answer your questions
      • send you information
      • for research activities, including the production of statistical reports (such aggregated information is not used to contact the subjects of the report)
      • send you surveys

      It is in Konveyor’s legitimate business interests to provide you with the information, communications, and services you request; to create a public record of the data and content produced by Konveyor’s services; and to maintain the integrity of that data and content for historical, scientific, and research purposes.

      Sharing Your Personal Data

      Unless you consent, Konveyor will never process or share the personal data you provide to us except as described below. Konveyor may disclose your personal data to third parties under any of the following circumstances:

      Your publicly available personal data in the Gerrit account system, as described above, is accessible by anyone unless you, as the account holder, opt out as already described in this Privacy Statement. As required to provide service, and for e-mail housing (as a consequence of uses already described in this Privacy Statement). It is in Konveyor’s legitimate business interest to provide all users an accurate record of data and content provided by Konveyor’s services, and to maintain the integrity of that data and content for historical, scientific, and research purposes. This data and content may include but is not limited to email, code changes, comments, and artifacts. As required by law (such as responding to a valid subpoena, warrant, audit, or agency action, or to prevent fraud). For research activities, including the production of statistical reports (such aggregated information is used to describe our services and is not used to contact the subjects of the report). Receiving E-Mail For your protection, Konveyor may contact you in the event that we find an issue that requires your immediate attention. Konveyor processes your personal data in these cases to fulfill and comply with its contractual obligations to you, to provide the services you have requested.

      Cookies and Other Browser Information

      Konveyor’s online services automatically capture IP addresses. We use IP addresses to help diagnose problems with our servers, to administer our website, and to help ensure the security of your interaction with our services. Your IP address is used to help identify you and your location, in order to provide you data and content from our services as quickly as possible. It is in Konveyor’s legitimate business interest to maximize the efficiency and effectiveness of its services for all users. As part of offering and providing customizable and personalized services, Konveyor uses cookies to store and sometimes track information about you. A cookie is a small amount of data that is sent to your browser from a Web server and stored on your computer’s hard drive. All sections of www.konveyor.io where you are prompted to log in or that are customizable require your browser to accept cookies.

      Generally, we use cookies to:

      • remind us of who you are and to access your gerrit account information (stored on our computers) in order to provide a better and more personalized service. This cookie is set when you register or “sign in” and is modified when you “sign out” of our services
      • estimate audience size. Each browser accessing Konveyor gerrit is given a unique cookie that is used to determine the extent of repeat usage and usage by a registered user versus by an unregistered user
      • measure certain traffic patterns, which areas of Konveyor’s network of websites you have visited, and your visiting patterns in the aggregate. We use this research to understand how our user’s habits are similar or different from one another so that we can make each new experience on www.konveyor.io a better one. We may use this information to better personalize the content, banners, and promotions you and other users will see on our sites.

      If you do not want your personal information to be stored by cookies, you can configure your browser so that it always rejects these cookies or asks you each time if you accept them or not. However, you must understand that the use of cookies may be necessary to provide certain services, and choosing to reject cookies will reduce the performance and functionality of the site. Your browser documentation includes instructions explaining how to enable, disable or delete cookies at the browser level (usually located in the “Help”, “Tools” or “Edit” facility).

      Our Commitment to Data Security

      Konveyor trains its administrators on our privacy policy guidelines and makes our privacy policy available to our partners. Our website uses Secure Socket Layer (SSL) technology, which encrypts your personal data when you send your personal information on the Gerrit website. In addition, Konveyor and its partners enter into confidentiality agreements which require that care and precautions be taken to prevent loss, misuse, or disclosure of your personal data.

      Public Forums Reminder

      Konveyor often makes chat rooms, forums, mailing lists, message boards, and/or news groups available to its users. Please remember that any information that is disclosed in these areas becomes public information. Exercise caution when deciding to disclose your personal data. Although we value individual ideas and encourage free expression, Konveyor reserves the right to take necessary action to preserve the integrity of these areas, such as removing any posting that is vulgar or inappropriate. It is in Konveyor’s legitimate business interests to provide all users an accurate record of data and content provided in the public forums it maintains and uses; to maintain the integrity of that data and content for historical, scientific, and research purposes; and to provide an environment for the free exchange of ideas relevant and constructive to the development and propagation of open source software.

      Our Commitment to Children’s Online Privacy

      Out of special concern for children’s privacy, Konveyor does not knowingly accept online personal information from children under the age of 13. Konveyor does not knowingly allow children under the age of 13 to become registered members of our sites. Konveyor does not knowingly collect or solicit personal information about children under 13. In the event that Konveyor ever decides to expand its intended site audience to include children under the age of 13, those specific web pages will, in accordance with the requirements of the Children’s Online Privacy Protection Act (COPPA), be clearly identified and provide an explicit privacy notice addressed to children under 13. In addition, Konveyor will provide an appropriate mechanism to obtain parental approval, allow parents to subsequently make changes to or request removal of their children’s personal information, and provide access to any other information as required by law.

      About Links to Other Sites

      This site contains links to other sites. Konveyor does not control the information collection of sites that can be reached through links from www.konveyor.io. If you have questions about the data collection procedures of linked sites, please contact these sites directly.

      Your Rights and Choices in the EEA

      Where the EU General Data Protection Regulation 2016/679 (“GDPR”) applies to the processing of your personal data, especially when you access the website from a country in the European Economic Area (“EEA”), you have the following rights, subject to some limitations, against Konveyor:

      The right to access your personal data; The right to rectify the personal data we hold about you; The right to erase your personal data; The right to restrict our use of your personal data; The right to object to our use of your personal data; The right to receive your personal data in a usable electronic format and transmit it to a third party (also known as the right of data portability); and The right to lodge a complaint with your local data protection authority. If you would like to exercise any of these rights, you may do so via our Personal Data Request Form. Please understand, however, the rights enumerated above are not absolute in all cases. Where the GDPR applies, you also have the right to withdraw any consent you have given to uses of your personal data. If you wish to withdraw consent that you have previously provided to Konveyor, you may do so via our privacy mail: legal@redhat.com. However, the withdrawal of consent will not affect the lawfulness of processing based on consent before its withdrawal.

      How to Contact Us

      If you have any questions about any of these practices or Konveyor’s use of your personal information, please feel free to contact us by email at legal@redhat.com. Konveyor will work with you to resolve any concerns you may have about this Statement.

      Changes to this Privacy Statement

      Konveyor reserves the right to change this Privacy Statement from time to time. If we do make changes, the revised Privacy Statement will be posted on the main project’s website. A notice will be posted on our homepage for 30 days whenever this privacy statement is changed in a material way.

      This Privacy Statement was last amended on October 28, 2020

      \ No newline at end of file +
      Konveyor is now a Cloud Native Computing Foundation (CNCF) Sandbox project

      Privacy Statement for the Konveyor Community

      Scope of This Notice

      This Privacy Statement is intended to describe the Konveyor Project’s privacy practices and provide information about the choices you have regarding the ways in which information collected by the Konveyor Project is used and disclosed. For convenience, the Konveyor Project is referred to in this document as “Konveyor”.

      Our Commitment to Privacy

      At Konveyor, your privacy is important to us. To better protect your privacy, we have provided this Statement explaining our information practices and the choices you can make about the way your personal information is collected, used and disclosed. To make this Statement easy to find, we have made it available on our homepage and at every location where personally-identifiable information may be requested.

      The Information We Collect

      This Privacy Statement applies to all information collected by or submitted to Konveyor, including personal data. “Personal data” is data that can be used to identify an individual.

      Konveyor collects personal data when:

      • you create a Gerrit and/or Bugzilla user account
      • you participate in surveys and evaluations
      • you submit questions or comments to us

      Konveyor may also collect personal data from individuals (with their consent) at conventions, trade shows and expositions.

      The types of personal data collected may include (but are not limited to):

      • your first and last name
      • your title and your company’s name
      • your e-mail address
      • any other identifier that permits Konveyor to make physical or online contact with you
      • any information that Konveyor collects online from you and maintains in association with your account, such as:
        • your GPG key ID
        • your SSH public key
        • your IRC nickname
        • your language preference
        • your timezone

      Publicly Available Personal Data

      In keeping with the open nature and spirit of Konveyor, some personal data attached to Konveyor accounts is made public by default. Specifically:

      • your first and last name
      • your email address
      • your language preference
      • your SSH public key
      • your timezone
      • your GPG key ID (if defined)
      • your IRC nickname (if defined)

      If you wish for this information to be kept private, you can opt-out of displaying this information publicly in your gerrit account preferences. If you choose to opt-out, Konveyor will still have access to this information, but it will not be displayed based on Gerrit capabilities to others, and will be considered Private. The only exception to this is for your email address, which may still be visible in some Konveyor services such as Bugzilla.

      Using (Processing) Your Personal Data Konveyor uses the personal data you provide to:

      • create and maintain your accounts
      • attribute data and content you produce directly and indirectly in our public-facing services
      • answer your questions
      • send you information
      • for research activities, including the production of statistical reports (such aggregated information is not used to contact the subjects of the report)
      • send you surveys

      It is in Konveyor’s legitimate business interests to provide you with the information, communications, and services you request; to create a public record of the data and content produced by Konveyor’s services; and to maintain the integrity of that data and content for historical, scientific, and research purposes.

      Sharing Your Personal Data

      Unless you consent, Konveyor will never process or share the personal data you provide to us except as described below. Konveyor may disclose your personal data to third parties under any of the following circumstances:

      Your publicly available personal data in the Gerrit account system, as described above, is accessible by anyone unless you, as the account holder, opt out as already described in this Privacy Statement. As required to provide service, and for e-mail housing (as a consequence of uses already described in this Privacy Statement). It is in Konveyor’s legitimate business interest to provide all users an accurate record of data and content provided by Konveyor’s services, and to maintain the integrity of that data and content for historical, scientific, and research purposes. This data and content may include but is not limited to email, code changes, comments, and artifacts. As required by law (such as responding to a valid subpoena, warrant, audit, or agency action, or to prevent fraud). For research activities, including the production of statistical reports (such aggregated information is used to describe our services and is not used to contact the subjects of the report). Receiving E-Mail For your protection, Konveyor may contact you in the event that we find an issue that requires your immediate attention. Konveyor processes your personal data in these cases to fulfill and comply with its contractual obligations to you, to provide the services you have requested.

      Cookies and Other Browser Information

      Konveyor’s online services automatically capture IP addresses. We use IP addresses to help diagnose problems with our servers, to administer our website, and to help ensure the security of your interaction with our services. Your IP address is used to help identify you and your location, in order to provide you data and content from our services as quickly as possible. It is in Konveyor’s legitimate business interest to maximize the efficiency and effectiveness of its services for all users. As part of offering and providing customizable and personalized services, Konveyor uses cookies to store and sometimes track information about you. A cookie is a small amount of data that is sent to your browser from a Web server and stored on your computer’s hard drive. All sections of www.konveyor.io where you are prompted to log in or that are customizable require your browser to accept cookies.

      Generally, we use cookies to:

      • remind us of who you are and to access your gerrit account information (stored on our computers) in order to provide a better and more personalized service. This cookie is set when you register or “sign in” and is modified when you “sign out” of our services
      • estimate audience size. Each browser accessing Konveyor gerrit is given a unique cookie that is used to determine the extent of repeat usage and usage by a registered user versus by an unregistered user
      • measure certain traffic patterns, which areas of Konveyor’s network of websites you have visited, and your visiting patterns in the aggregate. We use this research to understand how our user’s habits are similar or different from one another so that we can make each new experience on www.konveyor.io a better one. We may use this information to better personalize the content, banners, and promotions you and other users will see on our sites.

      If you do not want your personal information to be stored by cookies, you can configure your browser so that it always rejects these cookies or asks you each time if you accept them or not. However, you must understand that the use of cookies may be necessary to provide certain services, and choosing to reject cookies will reduce the performance and functionality of the site. Your browser documentation includes instructions explaining how to enable, disable or delete cookies at the browser level (usually located in the “Help”, “Tools” or “Edit” facility).

      Our Commitment to Data Security

      Konveyor trains its administrators on our privacy policy guidelines and makes our privacy policy available to our partners. Our website uses Secure Socket Layer (SSL) technology, which encrypts your personal data when you send your personal information on the Gerrit website. In addition, Konveyor and its partners enter into confidentiality agreements which require that care and precautions be taken to prevent loss, misuse, or disclosure of your personal data.

      Public Forums Reminder

      Konveyor often makes chat rooms, forums, mailing lists, message boards, and/or news groups available to its users. Please remember that any information that is disclosed in these areas becomes public information. Exercise caution when deciding to disclose your personal data. Although we value individual ideas and encourage free expression, Konveyor reserves the right to take necessary action to preserve the integrity of these areas, such as removing any posting that is vulgar or inappropriate. It is in Konveyor’s legitimate business interests to provide all users an accurate record of data and content provided in the public forums it maintains and uses; to maintain the integrity of that data and content for historical, scientific, and research purposes; and to provide an environment for the free exchange of ideas relevant and constructive to the development and propagation of open source software.

      Our Commitment to Children’s Online Privacy

      Out of special concern for children’s privacy, Konveyor does not knowingly accept online personal information from children under the age of 13. Konveyor does not knowingly allow children under the age of 13 to become registered members of our sites. Konveyor does not knowingly collect or solicit personal information about children under 13. In the event that Konveyor ever decides to expand its intended site audience to include children under the age of 13, those specific web pages will, in accordance with the requirements of the Children’s Online Privacy Protection Act (COPPA), be clearly identified and provide an explicit privacy notice addressed to children under 13. In addition, Konveyor will provide an appropriate mechanism to obtain parental approval, allow parents to subsequently make changes to or request removal of their children’s personal information, and provide access to any other information as required by law.

      About Links to Other Sites

      This site contains links to other sites. Konveyor does not control the information collection of sites that can be reached through links from www.konveyor.io. If you have questions about the data collection procedures of linked sites, please contact these sites directly.

      Your Rights and Choices in the EEA

      Where the EU General Data Protection Regulation 2016/679 (“GDPR”) applies to the processing of your personal data, especially when you access the website from a country in the European Economic Area (“EEA”), you have the following rights, subject to some limitations, against Konveyor:

      The right to access your personal data; The right to rectify the personal data we hold about you; The right to erase your personal data; The right to restrict our use of your personal data; The right to object to our use of your personal data; The right to receive your personal data in a usable electronic format and transmit it to a third party (also known as the right of data portability); and The right to lodge a complaint with your local data protection authority. If you would like to exercise any of these rights, you may do so via our Personal Data Request Form. Please understand, however, the rights enumerated above are not absolute in all cases. Where the GDPR applies, you also have the right to withdraw any consent you have given to uses of your personal data. If you wish to withdraw consent that you have previously provided to Konveyor, you may do so via our privacy mail: legal@redhat.com. However, the withdrawal of consent will not affect the lawfulness of processing based on consent before its withdrawal.

      How to Contact Us

      If you have any questions about any of these practices or Konveyor’s use of your personal information, please feel free to contact us by email at legal@redhat.com. Konveyor will work with you to resolve any concerns you may have about this Statement.

      Changes to this Privacy Statement

      Konveyor reserves the right to change this Privacy Statement from time to time. If we do make changes, the revised Privacy Statement will be posted on the main project’s website. A notice will be posted on our homepage for 30 days whenever this privacy statement is changed in a material way.

      This Privacy Statement was last amended on October 28, 2020

      \ No newline at end of file diff --git a/blog/index.html b/blog/index.html index 07d76b45..9992a716 100644 --- a/blog/index.html +++ b/blog/index.html @@ -52,5 +52,5 @@ } } }) -
      Konveyor is now a Cloud Native Computing Foundation (CNCF) Sandbox project

      Konveyor Blog

      Jul 11, 2023

      Modernize Petclinic App to Kubernetes Using Konveyor

      Konveyor aims to surface insights on applications at scale to empower enterprise users to make better-informed decisions related to modernization activities. This tutorial focuses on addressing edge case issues with Hazelcast during Kubernetes migration, emphasizing the benefits of creating custom rules and sharing knowledge to streamline future modernization efforts.

      Jul 6, 2023

      Konveyor v0.2.1 Release Announcement

      Konveyor v0.2.1 Release Announcement

      May 26, 2023

      Reflecting on Large-Scale Cloud-Native Modernizations at KubeCon 23

      Migrating large infrastructures from an on-premise, monolithic, traditional IT management approach to a modern cloud-native Kubernetes-based ecosystem is a daunting task. Christopher Nuland (Konveyor Ambassador) led a conversation with Jared Burk and Valentina Rodriguez Sosa, Red Hat; James Bench, Maximus - about the different migrations they have completed and the challenges they experienced.

      Oct 20, 2022

      Community Update: Konveyor Refocuses Efforts on Replatforming and Refactoring Use Cases

      We recently revealed upcoming changes to the Konveyor Project. These adjustments are designed to solve the most important application modernizations problem better and to encourage participation with our community.

      Sep 14, 2022

      Tackle 2.1 release

      New features include a new report that gives details about the application data layer, easier CSV importing, bulk deletion of applications, and a more streamlined user experience.

      Aug 5, 2022

      Konveyor is now a Cloud Native Computing Foundation (CNCF) Sandbox project

      Big news! Konveyor was recently accepted as a Cloud Native Computing Foundation (CNCF) Sandbox project.

      Jul 7, 2022

      A Method to Measure and Manage Technical Debt

      we demonstrate that not only is technical debt key to making decisions regarding any specific application, it is also important when attempting to prioritize work between multiple applications.

      \ No newline at end of file +
      Konveyor is now a Cloud Native Computing Foundation (CNCF) Sandbox project

      Konveyor Blog

      Sep 21, 2023

      One Year in the CNCF Sandbox- Konveyor's Reflective Journey

      It has been an exceptional year for Konveyor since its admission into the CNCF in July 2022. Since then, the project has undergone a series of transformative changes and remarkable achievements, guided by a newly updated charter that has refocused Konveyor's mission towards refactoring and replatforming legacy applications. In this post, we invite you to join us on a journey down memory lane as we celebrate the numerous milestones, both big and small, that our dedicated contributors have accomplished over the past year.

      Jul 11, 2023

      Modernize Petclinic App to Kubernetes Using Konveyor

      Konveyor aims to surface insights on applications at scale to empower enterprise users to make better-informed decisions related to modernization activities. This tutorial focuses on addressing edge case issues with Hazelcast during Kubernetes migration, emphasizing the benefits of creating custom rules and sharing knowledge to streamline future modernization efforts.

      Jul 6, 2023

      Konveyor v0.2.1 Release Announcement

      Konveyor v0.2.1 Release Announcement

      May 26, 2023

      Reflecting on Large-Scale Cloud-Native Modernizations at KubeCon 23

      Migrating large infrastructures from an on-premise, monolithic, traditional IT management approach to a modern cloud-native Kubernetes-based ecosystem is a daunting task. Christopher Nuland (Konveyor Ambassador) led a conversation with Jared Burk and Valentina Rodriguez Sosa, Red Hat; James Bench, Maximus + about the different migrations they have completed and the challenges they experienced.

      Oct 20, 2022

      Community Update: Konveyor Refocuses Efforts on Replatforming and Refactoring Use Cases

      We recently revealed upcoming changes to the Konveyor Project. These adjustments are designed to solve the most important application modernizations problem better and to encourage participation with our community.

      Sep 14, 2022

      Tackle 2.1 release

      New features include a new report that gives details about the application data layer, easier CSV importing, bulk deletion of applications, and a more streamlined user experience.

      Aug 5, 2022

      Konveyor is now a Cloud Native Computing Foundation (CNCF) Sandbox project

      Big news! Konveyor was recently accepted as a Cloud Native Computing Foundation (CNCF) Sandbox project.

      \ No newline at end of file diff --git a/blog/konveyor-community-hackfest/index.html b/blog/konveyor-community-hackfest/index.html index c1e60400..0da4e68c 100644 --- a/blog/konveyor-community-hackfest/index.html +++ b/blog/konveyor-community-hackfest/index.html @@ -52,4 +52,4 @@ } } }) -
      Konveyor is now a Cloud Native Computing Foundation (CNCF) Sandbox project

      Dec 21, 2021

      Konveyor Community HackFest

      Tags:

      January 31–February 4, 2022. 9 a.m.–5 p.m. EST each day

      Get free hands-on experience migrating different workload types to Kubernetes with open source tools and community engineer support. Register to get the calendar invite.

      The Konveyor community has developed multiple use cases for you to learn time- and cost-efficient ways to migrate to Kubernetes. During this HackFest, if something is missing, not working as expected, or you simply get stuck — you can open a GitHub issue or get support from the community engineers.

      By joining, you’ll help improve the effectiveness and usability of the open source tools in the Konveyor Community. All tools you can continue to leverage for free after the event is over to migrate to Kubernetes.

      You’ll walk away knowing how to:

      • Rehost apps between Kubernetes clusters and automating with GitOps using the tool Crane

      • Replatform apps to Kubernetes from other container orchestration platforms with tool Move2Kube

      • Rehost virtual machines to KubeVirt with tool Forklift

      • Assess, analyze, and refactor applications to Kubernetes with tool Tackle.

      Each day will be dedicated to 1 or 2 use cases addressed by our tools. You can participate each day or the day we focus on the use case most relevant to you.

      Register on this form to get the calendar invite and full agenda once it is finalized.

      \ No newline at end of file +
      Konveyor is now a Cloud Native Computing Foundation (CNCF) Sandbox project

      Dec 21, 2021

      Konveyor Community HackFest

      Tags:

      January 31–February 4, 2022. 9 a.m.–5 p.m. EST each day

      Get free hands-on experience migrating different workload types to Kubernetes with open source tools and community engineer support. Register to get the calendar invite.

      The Konveyor community has developed multiple use cases for you to learn time- and cost-efficient ways to migrate to Kubernetes. During this HackFest, if something is missing, not working as expected, or you simply get stuck — you can open a GitHub issue or get support from the community engineers.

      By joining, you’ll help improve the effectiveness and usability of the open source tools in the Konveyor Community. All tools you can continue to leverage for free after the event is over to migrate to Kubernetes.

      You’ll walk away knowing how to:

      • Rehost apps between Kubernetes clusters and automating with GitOps using the tool Crane

      • Replatform apps to Kubernetes from other container orchestration platforms with tool Move2Kube

      • Rehost virtual machines to KubeVirt with tool Forklift

      • Assess, analyze, and refactor applications to Kubernetes with tool Tackle.

      Each day will be dedicated to 1 or 2 use cases addressed by our tools. You can participate each day or the day we focus on the use case most relevant to you.

      Register on this form to get the calendar invite and full agenda once it is finalized.

      \ No newline at end of file diff --git a/blog/konveyor-is-a-cncf-sandbox-project/index.html b/blog/konveyor-is-a-cncf-sandbox-project/index.html index c522741a..3441ff0b 100644 --- a/blog/konveyor-is-a-cncf-sandbox-project/index.html +++ b/blog/konveyor-is-a-cncf-sandbox-project/index.html @@ -52,4 +52,4 @@ } } }) -
      Konveyor is now a Cloud Native Computing Foundation (CNCF) Sandbox project

      Aug 5, 2022

      Konveyor is now a Cloud Native Computing Foundation (CNCF) Sandbox project

      Tags:

      Big news! Konveyor was recently accepted as a Cloud Native Computing Foundation (CNCF) Sandbox project 🎉

      Why are we so excited about this?

      This is a huge milestone in our mission to accelerate the movement of applications to run on Kubernetes with an open-source approach. With the added credibility of our sandbox status, we can more easily attract and convince others to adopt and contribute to Konveyor. The result will be more effective open source tools that everyone can use to adopt Kubernetes and cloud-native technology faster!

      What happens now?

      We’re trying to get the word out about our new status.

      With regards to tools, we’re rethinking where to focus based on interest and usage. More on that to come later. For now, sharing the news with your network would be the most helpful.

      And lastly, thank you to all involved for helping this happen:

      • Karena Angell and Josh Berkus for guiding us through the application process.
      • IBM Research and Red Hat for contributing tools and helping to spread the word about the community.
      • Microsoft for contributing PRs and providing feedback to the community.
      • And to all of you on this email list for attending meetups, using the tools, giving us feedback, and spreading the word.

      Happy migrating,

      Konveyor team

      \ No newline at end of file +
      Konveyor is now a Cloud Native Computing Foundation (CNCF) Sandbox project

      Aug 5, 2022

      Konveyor is now a Cloud Native Computing Foundation (CNCF) Sandbox project

      Tags:

      Big news! Konveyor was recently accepted as a Cloud Native Computing Foundation (CNCF) Sandbox project 🎉

      Why are we so excited about this?

      This is a huge milestone in our mission to accelerate the movement of applications to run on Kubernetes with an open-source approach. With the added credibility of our sandbox status, we can more easily attract and convince others to adopt and contribute to Konveyor. The result will be more effective open source tools that everyone can use to adopt Kubernetes and cloud-native technology faster!

      What happens now?

      We’re trying to get the word out about our new status.

      With regards to tools, we’re rethinking where to focus based on interest and usage. More on that to come later. For now, sharing the news with your network would be the most helpful.

      And lastly, thank you to all involved for helping this happen:

      • Karena Angell and Josh Berkus for guiding us through the application process.
      • IBM Research and Red Hat for contributing tools and helping to spread the word about the community.
      • Microsoft for contributing PRs and providing feedback to the community.
      • And to all of you on this email list for attending meetups, using the tools, giving us feedback, and spreading the word.

      Happy migrating,

      Konveyor team

      \ No newline at end of file diff --git a/blog/measure-manage-technical-debt/index.html b/blog/measure-manage-technical-debt/index.html index c6f1fe1f..c093b351 100644 --- a/blog/measure-manage-technical-debt/index.html +++ b/blog/measure-manage-technical-debt/index.html @@ -61,4 +61,4 @@ Graph show Complexity vs. Risk -

      The overall debt levels were then converted into currency units, depicting the level of investment required to add new functionality into the system, e.g. only $0.1 of every $1 of any investment will go into innovation due to architectural technical debt. This is intended to help organizations build a business case for handling and removing architectural technical debt from their applications.

      We have shown a method to measure technical debt of an application based on the dependencies between its classes. We have successfully used this method to both identify local issues which cause technical debt as well as providing a global score, comparable between applications. By employing this method, organizations can successfully assess and manage the technical debt in their software which will lead to a better overall decision making process.

        Bio: Ori Saporta co-founded vFunction and serves as its Systems Architect. Prior to founding vFunction, Ori was the lead Systems Architect of WatchDox until its acquisition by Blackberry, where he continued to serve in the role of Distinguished Systems Architect. Prior to that, Ori was a Systems Architect at Israeli’s Intelligence Core Technology Unit (8200). Ori has a BSc in Computer Engineering from Tel-Aviv University and an MSc in Computer Science from the same institute for which his thesis subject was “Testing and Optimizing Data-Structure Implementations Under the RC11 Memory Model.”

          1. Nord, Robert L., et al. “In search of a metric for managing architectural technical debt.” 2012 Joint Working IEEE/IFIP Conference on Software Architecture and European Conference on Software Architecture. IEEE, 2012.↩
          2. Wikipedia: God object.↩
          \ No newline at end of file +

          The overall debt levels were then converted into currency units, depicting the level of investment required to add new functionality into the system, e.g. only $0.1 of every $1 of any investment will go into innovation due to architectural technical debt. This is intended to help organizations build a business case for handling and removing architectural technical debt from their applications.

          We have shown a method to measure technical debt of an application based on the dependencies between its classes. We have successfully used this method to both identify local issues which cause technical debt as well as providing a global score, comparable between applications. By employing this method, organizations can successfully assess and manage the technical debt in their software which will lead to a better overall decision making process.

            Bio: Ori Saporta co-founded vFunction and serves as its Systems Architect. Prior to founding vFunction, Ori was the lead Systems Architect of WatchDox until its acquisition by Blackberry, where he continued to serve in the role of Distinguished Systems Architect. Prior to that, Ori was a Systems Architect at Israeli’s Intelligence Core Technology Unit (8200). Ori has a BSc in Computer Engineering from Tel-Aviv University and an MSc in Computer Science from the same institute for which his thesis subject was “Testing and Optimizing Data-Structure Implementations Under the RC11 Memory Model.”

              1. Nord, Robert L., et al. “In search of a metric for managing architectural technical debt.” 2012 Joint Working IEEE/IFIP Conference on Software Architecture and European Conference on Software Architecture. IEEE, 2012.↩
              2. Wikipedia: God object.↩
              \ No newline at end of file diff --git a/blog/metrics-driven-approach-to-transformation/index.html b/blog/metrics-driven-approach-to-transformation/index.html index cd9b7bcd..37753b61 100644 --- a/blog/metrics-driven-approach-to-transformation/index.html +++ b/blog/metrics-driven-approach-to-transformation/index.html @@ -61,4 +61,4 @@ Software delivery metrics -

              Finally, the authors enumerated the various practices and capabilities that drive software delivery performance as measured this way: test automation, deployment automation, loosely coupled architecture, and monitoring, among others.

              What this means is that we have specific measures that adopters of container platforms (among other emerging technologies) can use to guide how the technology is adopted in ways that can lead to better organizational performance. And we have a set of practices that can be applied against this technology backdrop, using containers and container platform as accelerators of those practices when possible.

              The focus for the authors is on global performance, not local optimization, and on “outcomes not output,” so the organization rewards activities that matter, rather than sheer volume of activity. This last point is crucial. In an earlier post, I wrote about app onboarding to OpenShift. Taken to the extreme, a myopic focus on the percentage of the portfolio or number of apps migrated to X (containers, Kubernetes, OpenShift, AWS, “The Cloud”) is a focus on outputs not outcomes. It’s a measure that seems to indicate progress but does not directly determine the success of the cloud adoption program as a whole, success that must involve some wider notion of commercial or noncommercial performance.

              Put another way, cloud platforms do not automatically confer continuous delivery capabilities upon their adopters. They enable them. They accelerate them. But without changing the way we deliver software as an organization — the way we work — cloud technology (or any other newly introduced technology) will probably fail to match its promise.

              I will be writing more about how we put a metrics-based approach into practice with our customers in upcoming posts, starting with an update on how we’ve begun to capture these metrics in dashboards to keep stakeholders and project participants aligned to meaningful goals.

              \ No newline at end of file +

              Finally, the authors enumerated the various practices and capabilities that drive software delivery performance as measured this way: test automation, deployment automation, loosely coupled architecture, and monitoring, among others.

              What this means is that we have specific measures that adopters of container platforms (among other emerging technologies) can use to guide how the technology is adopted in ways that can lead to better organizational performance. And we have a set of practices that can be applied against this technology backdrop, using containers and container platform as accelerators of those practices when possible.

              The focus for the authors is on global performance, not local optimization, and on “outcomes not output,” so the organization rewards activities that matter, rather than sheer volume of activity. This last point is crucial. In an earlier post, I wrote about app onboarding to OpenShift. Taken to the extreme, a myopic focus on the percentage of the portfolio or number of apps migrated to X (containers, Kubernetes, OpenShift, AWS, “The Cloud”) is a focus on outputs not outcomes. It’s a measure that seems to indicate progress but does not directly determine the success of the cloud adoption program as a whole, success that must involve some wider notion of commercial or noncommercial performance.

              Put another way, cloud platforms do not automatically confer continuous delivery capabilities upon their adopters. They enable them. They accelerate them. But without changing the way we deliver software as an organization — the way we work — cloud technology (or any other newly introduced technology) will probably fail to match its promise.

              I will be writing more about how we put a metrics-based approach into practice with our customers in upcoming posts, starting with an update on how we’ve begun to capture these metrics in dashboards to keep stakeholders and project participants aligned to meaningful goals.

              \ No newline at end of file diff --git a/blog/modernization-report/index.html b/blog/modernization-report/index.html index 2293a694..de95a3fb 100644 --- a/blog/modernization-report/index.html +++ b/blog/modernization-report/index.html @@ -52,4 +52,4 @@ } } }) -
              Konveyor is now a Cloud Native Computing Foundation (CNCF) Sandbox project

              State of Application Modernization Report 2022

              by Gordon Haff

              Both anecdotes and past surveys tell us that organizations are modernizing their applications. We wanted to dig deeper into the specifics. To do so, Konveyor community contributor Red Hat sponsored a survey of 600 IT decision makers (ITDM), backend developers, and software architects in the US, UK, and English-speaking Asia-Pacific (APAC). We surveyed these respondents, drawn from third-party databases, in October and November of 2021. Their companies had to have an internal app dev team and had to be using or planning to use hybrid cloud or multicloud as well as containers (the overwhelming majority were already using both). Here are some of the things they told us.

              Modernization is happening quickly

              Companies plan for more than half of their custom applications to be modernized within the next year.

              We sought out respondents who were modernizing or planning to modernize their custom apps in some manner, so it’s no surprise that everyone we surveyed is modernizing. What’s perhaps less expected is how quickly they’re planning to modernize. Companies are planning to modernize over half of their custom applications during the next year and over a quarter during the next six months. Only 20% expected the modernization to take more than two years.

              Does that seem a bit… optimistic? It does. Indeed, as was something of a theme throughout this survey, developers were less confident than their ITDM and architect counterparts that modernization would be either quick or straightforward.

              The barriers cited by respondents provide additional evidence that modernization projects won’t always be smooth sailing. All regions except the UK said that resistance to change was the top barrier—and in the UK it was still near the top. The fact that this is a cultural challenge far more than a technical one suggests that overcoming such a barrier may be difficult and require senior management buy-in. Other top barriers were related concerns like time constraints, cost and budget constraints, and lack of skilled resources. Skills shortages in particular are a common theme almost across the board when we conduct surveys about important IT initiatives.

              However, even if you think that a lot of modernization projects are likely to slip out, the data certainly points to an intent to rapidly modernize.

              There’s no single app modernization strategy

              Companies intend to replatform, refactor, or repurchase just over half of their custom legacy applications.

              In considering app modernization strategies, we presented survey respondents with six choices, the widely used six Rs. These are:

              • Retire: Sunset or decommission applications that are no longer needed
              • Retain: Leave critical applications as-is until refactoring is required
              • Rehost: Copy applications to a cloud (whether hosted or on-prem) with minimal changes, i.e. “lift and shift”
              • Replatform: Use a cloud migration to upgrade operating systems, databases, and other components as needed in order to cloud-enable applications without changing core application code or architecture
              • Refactor: Re-architect as cloud-native, for example, by containerizing workloads or moving them to a serverless architecture
              • Repurchase: Move from perpetual licenses to a Software-as-a-Service (SaaS) model

              That’s quite the range of options and they’re all being used to significant degrees. Retire and retain were each about half as popular than the four other options — which each captured about 20% of the applications being modernized. The overall story is definitely about matching the application modernization strategy to a given workload and company need rather than there being a single dominant approach across companies.

              We again see developers being more cautious or pessimistic about more aggressive modernization approaches; they were more likely to intend to rehost relative to ITDMs and architects. We sometimes hear about “resume-driven development,” whereby developers supposedly want to gain experience in new technologies, even if doing so increases complexity. However, the developers in our survey were more likely to favor lower risk and lower effort approaches.

              We also found that refactoring, which is the most involved modernization approach, is almost always a two-step approach. 90% of those who plan to refactor any legacy apps intend to replatform them first.

              The US is further along than others

              USUKAPAC
              Unique Definitions of App ModernizationUsing microservices architecture in the cloudImproving CI/CDImproving CI/CD
              Unique Reasons for App ModernizationDecrease costsDecrease costsImprove security improve customer experience
              Unique Barriers
              • Difficulty determining the right approach
              • Do no see the value of modernizing
              		Have not faces any barriersHave not faced any barriers
              Unique ChallengesDifficulty determining the right approachNo differentiating challengesNo differentiating challenges
              Unique Success MeasuresDecreased costincreased customer satisfactionImproved security increased customer satisfaction
              Legacy App StrategyMore likely to retire or retain applicationsMore likely to rehost or repurchase applicationsMost likely to rehost or repurchase applications
              Unique App Modernization PrioritiesNo differentiating PrioritiesData/analytics/BI applications
              • Customer-facing applications
              • Data/analytics/BI applications

              We don’t generally find striking differences between regions but we do sometimes see more subtle ones that form something of a pattern, as was the case here.

              In this case, we see the US uniquely defining app modernization as “Using microservices architecture in the cloud” while the other two regions defined it as “Improving CI/CD.” This suggests that the US is further along in app modernization. Having a well-developed CI/CD pipeline is foundational to microservices and other cloud-native technology approaches.

              We see something similar crop up with respect to barriers and challenges. The UK and APAC haven’t faced any barriers. It’s reasonable to assume that’s because they haven’t gotten far enough into the process yet. By contrast, the US is focused on the “Difficulty determining the right approach,” suggesting that they’re actively figuring out the best way to implement a modernization strategy across their application portfolio.

              Increasing scalability and reliability trump cost reductions

              Companies plan to measure success of application modernization base on increased reliability and increased scalability.

              How are companies going to measure the success of their application modernizations? Decreased costs are one factor. Costs always matter to at least some degree; ask anyone who has ever owned a budget. But increased reliability (especially in the US) and scalability were at the top of the list overall, with security high up as well.

              This was a question that had significant regional differences. Improving security was a significantly higher-ranked measure in APAC than in other regions and even edged out increased scalability there. APAC was also much more likely to measure increased customer satisfaction—especially relative to the US.

              AI/ML, data caching, and high performance computing on the upswing

              More companies expect to have AI/ML software, data caching tools, and high performance computing workloads in place in the next 2 years.

              While traditional workloads such as web servers, business process applications, and databases are the most common today, they’re not where workload growth is expected to be over the next two years. That would be AI/ML software, data caching (think Redis), and high performance computing, which are expected to grow at least 20% during that period. Analytics falls in between the two groups both in terms of level of usage today and its expected rate of growth.

              Thus, many new applications and application architectures are likely to be in emerging technology areas which include these high growth workloads. While most of the workloads were fairly consistent across regions, AI/ML in the US (68%) was markedly higher than in the UK (57%) which was higher than in APAC (43%).

              Is there a public cloud backlash?

              Companies expect a shift from public cloud toward private cloud deployment 2 years from now, especially in the UK and APAC.

              The overwhelming majority of the companies we surveyed run at least some of their production applications on a public cloud although a significant number also run on a private cloud—whether on-premise, off-premise, or both.

              The most striking thing about these numbers though is where they’re headed. The 98% of companies that have at least some production workloads on a public cloud today is expected to drop ten points over the next two years to 88%. This drop is almost entirely attributable to the UK and APAC with the US dropping only one point. In APAC specifically, a full 26% of companies plan to stop using public clouds for production workloads; most of those workloads would appear to be going to off-premise private clouds which have a commensurately large expected increase.

              What’s going on? Are public clouds falling out of favor?

              There’s some anecdotal evidence that data egress and a general lack of cost predictability have driven some companies to repatriate certain applications to private clouds. Furthermore, edge computing architectures distribute workloads so as to bring compute resources closer to data and user services. (Although they still often have a cloud component, whether on a public cloud or on-premise.)

              However, in the US, the percentage of companies with one or more production workloads on a public cloud is expected to stay essentially flat. This suggests that the significant expected shift in the UK and APAC numbers probably isn’t explained by cost and edge computing alone.

              Based on other surveys we’ve conducted, those other reasons may relate to data privacy, data security, and data sovereignty concerns. It’s not a stretch to imagine that these concerns might be heightened in the UK and APAC, especially in light of the fact that the three large global public cloud providers are all headquartered in the US.

              The above notwithstanding, however, backlash is probably too strong a term. Rather, with 77% already having a hybrid cloud infrastructure, the results suggest that companies are just increasingly sophisticated in placing workloads on the best kind of infrastructure for the purpose rather than taking more of a one-size-fits-all approach.

              Slide deck with all findings

              State of application modernization 2022 from Konveyor Community

                Gordon Haff is Technology Advocate at Red Hat where he works on emerging technology strategy; writes about tech, trends, and their business impact; and is a frequent speaker at customer and industry events. Among the topics he works on are edge, blockchain, AI, quantum, cloud-native platforms, and next-generation application architectures. His books include From Pots and Vats to Programs and Apps and How Open Source Ate Software. His current podcast is Innovate @ Open. Prior to Red Hat, as an industry analyst, Gordon wrote hundreds of research notes, was frequently quoted in major publications on a wide range of IT topics, and advised clients on product and marketing strategies.

                \ No newline at end of file +
                Konveyor is now a Cloud Native Computing Foundation (CNCF) Sandbox project

                State of Application Modernization Report 2022

                by Gordon Haff

                Both anecdotes and past surveys tell us that organizations are modernizing their applications. We wanted to dig deeper into the specifics. To do so, Konveyor community contributor Red Hat sponsored a survey of 600 IT decision makers (ITDM), backend developers, and software architects in the US, UK, and English-speaking Asia-Pacific (APAC). We surveyed these respondents, drawn from third-party databases, in October and November of 2021. Their companies had to have an internal app dev team and had to be using or planning to use hybrid cloud or multicloud as well as containers (the overwhelming majority were already using both). Here are some of the things they told us.

                Modernization is happening quickly

                Companies plan for more than half of their custom applications to be modernized within the next year.

                We sought out respondents who were modernizing or planning to modernize their custom apps in some manner, so it’s no surprise that everyone we surveyed is modernizing. What’s perhaps less expected is how quickly they’re planning to modernize. Companies are planning to modernize over half of their custom applications during the next year and over a quarter during the next six months. Only 20% expected the modernization to take more than two years.

                Does that seem a bit… optimistic? It does. Indeed, as was something of a theme throughout this survey, developers were less confident than their ITDM and architect counterparts that modernization would be either quick or straightforward.

                The barriers cited by respondents provide additional evidence that modernization projects won’t always be smooth sailing. All regions except the UK said that resistance to change was the top barrier—and in the UK it was still near the top. The fact that this is a cultural challenge far more than a technical one suggests that overcoming such a barrier may be difficult and require senior management buy-in. Other top barriers were related concerns like time constraints, cost and budget constraints, and lack of skilled resources. Skills shortages in particular are a common theme almost across the board when we conduct surveys about important IT initiatives.

                However, even if you think that a lot of modernization projects are likely to slip out, the data certainly points to an intent to rapidly modernize.

                There’s no single app modernization strategy

                Companies intend to replatform, refactor, or repurchase just over half of their custom legacy applications.

                In considering app modernization strategies, we presented survey respondents with six choices, the widely used six Rs. These are:

                • Retire: Sunset or decommission applications that are no longer needed
                • Retain: Leave critical applications as-is until refactoring is required
                • Rehost: Copy applications to a cloud (whether hosted or on-prem) with minimal changes, i.e. “lift and shift”
                • Replatform: Use a cloud migration to upgrade operating systems, databases, and other components as needed in order to cloud-enable applications without changing core application code or architecture
                • Refactor: Re-architect as cloud-native, for example, by containerizing workloads or moving them to a serverless architecture
                • Repurchase: Move from perpetual licenses to a Software-as-a-Service (SaaS) model

                That’s quite the range of options and they’re all being used to significant degrees. Retire and retain were each about half as popular than the four other options — which each captured about 20% of the applications being modernized. The overall story is definitely about matching the application modernization strategy to a given workload and company need rather than there being a single dominant approach across companies.

                We again see developers being more cautious or pessimistic about more aggressive modernization approaches; they were more likely to intend to rehost relative to ITDMs and architects. We sometimes hear about “resume-driven development,” whereby developers supposedly want to gain experience in new technologies, even if doing so increases complexity. However, the developers in our survey were more likely to favor lower risk and lower effort approaches.

                We also found that refactoring, which is the most involved modernization approach, is almost always a two-step approach. 90% of those who plan to refactor any legacy apps intend to replatform them first.

                The US is further along than others

                USUKAPAC
                Unique Definitions of App ModernizationUsing microservices architecture in the cloudImproving CI/CDImproving CI/CD
                Unique Reasons for App ModernizationDecrease costsDecrease costsImprove security improve customer experience
                Unique Barriers
                • Difficulty determining the right approach
                • Do no see the value of modernizing
                		Have not faces any barriersHave not faced any barriers
                Unique ChallengesDifficulty determining the right approachNo differentiating challengesNo differentiating challenges
                Unique Success MeasuresDecreased costincreased customer satisfactionImproved security increased customer satisfaction
                Legacy App StrategyMore likely to retire or retain applicationsMore likely to rehost or repurchase applicationsMost likely to rehost or repurchase applications
                Unique App Modernization PrioritiesNo differentiating PrioritiesData/analytics/BI applications
                • Customer-facing applications
                • Data/analytics/BI applications

                We don’t generally find striking differences between regions but we do sometimes see more subtle ones that form something of a pattern, as was the case here.

                In this case, we see the US uniquely defining app modernization as “Using microservices architecture in the cloud” while the other two regions defined it as “Improving CI/CD.” This suggests that the US is further along in app modernization. Having a well-developed CI/CD pipeline is foundational to microservices and other cloud-native technology approaches.

                We see something similar crop up with respect to barriers and challenges. The UK and APAC haven’t faced any barriers. It’s reasonable to assume that’s because they haven’t gotten far enough into the process yet. By contrast, the US is focused on the “Difficulty determining the right approach,” suggesting that they’re actively figuring out the best way to implement a modernization strategy across their application portfolio.

                Increasing scalability and reliability trump cost reductions

                Companies plan to measure success of application modernization base on increased reliability and increased scalability.

                How are companies going to measure the success of their application modernizations? Decreased costs are one factor. Costs always matter to at least some degree; ask anyone who has ever owned a budget. But increased reliability (especially in the US) and scalability were at the top of the list overall, with security high up as well.

                This was a question that had significant regional differences. Improving security was a significantly higher-ranked measure in APAC than in other regions and even edged out increased scalability there. APAC was also much more likely to measure increased customer satisfaction—especially relative to the US.

                AI/ML, data caching, and high performance computing on the upswing

                More companies expect to have AI/ML software, data caching tools, and high performance computing workloads in place in the next 2 years.

                While traditional workloads such as web servers, business process applications, and databases are the most common today, they’re not where workload growth is expected to be over the next two years. That would be AI/ML software, data caching (think Redis), and high performance computing, which are expected to grow at least 20% during that period. Analytics falls in between the two groups both in terms of level of usage today and its expected rate of growth.

                Thus, many new applications and application architectures are likely to be in emerging technology areas which include these high growth workloads. While most of the workloads were fairly consistent across regions, AI/ML in the US (68%) was markedly higher than in the UK (57%) which was higher than in APAC (43%).

                Is there a public cloud backlash?

                Companies expect a shift from public cloud toward private cloud deployment 2 years from now, especially in the UK and APAC.

                The overwhelming majority of the companies we surveyed run at least some of their production applications on a public cloud although a significant number also run on a private cloud—whether on-premise, off-premise, or both.

                The most striking thing about these numbers though is where they’re headed. The 98% of companies that have at least some production workloads on a public cloud today is expected to drop ten points over the next two years to 88%. This drop is almost entirely attributable to the UK and APAC with the US dropping only one point. In APAC specifically, a full 26% of companies plan to stop using public clouds for production workloads; most of those workloads would appear to be going to off-premise private clouds which have a commensurately large expected increase.

                What’s going on? Are public clouds falling out of favor?

                There’s some anecdotal evidence that data egress and a general lack of cost predictability have driven some companies to repatriate certain applications to private clouds. Furthermore, edge computing architectures distribute workloads so as to bring compute resources closer to data and user services. (Although they still often have a cloud component, whether on a public cloud or on-premise.)

                However, in the US, the percentage of companies with one or more production workloads on a public cloud is expected to stay essentially flat. This suggests that the significant expected shift in the UK and APAC numbers probably isn’t explained by cost and edge computing alone.

                Based on other surveys we’ve conducted, those other reasons may relate to data privacy, data security, and data sovereignty concerns. It’s not a stretch to imagine that these concerns might be heightened in the UK and APAC, especially in light of the fact that the three large global public cloud providers are all headquartered in the US.

                The above notwithstanding, however, backlash is probably too strong a term. Rather, with 77% already having a hybrid cloud infrastructure, the results suggest that companies are just increasingly sophisticated in placing workloads on the best kind of infrastructure for the purpose rather than taking more of a one-size-fits-all approach.

                Slide deck with all findings

                State of application modernization 2022 from Konveyor Community

                  Gordon Haff is Technology Advocate at Red Hat where he works on emerging technology strategy; writes about tech, trends, and their business impact; and is a frequent speaker at customer and industry events. Among the topics he works on are edge, blockchain, AI, quantum, cloud-native platforms, and next-generation application architectures. His books include From Pots and Vats to Programs and Apps and How Open Source Ate Software. His current podcast is Innovate @ Open. Prior to Red Hat, as an industry analyst, Gordon wrote hundreds of research notes, was frequently quoted in major publications on a wide range of IT topics, and advised clients on product and marketing strategies.

                  \ No newline at end of file diff --git a/blog/modernize-petclinic-to-k8s-using-konveyor/index.html b/blog/modernize-petclinic-to-k8s-using-konveyor/index.html index 208a149c..854ec115 100644 --- a/blog/modernize-petclinic-to-k8s-using-konveyor/index.html +++ b/blog/modernize-petclinic-to-k8s-using-konveyor/index.html @@ -246,4 +246,4 @@ Refactored App -

                  Click here to watch the video for part 3 in action - Refractor and Deploy to K8s

                  Conclusion

                  Get involved in the Konveyor Community

                  The Konveyor project is actively seeking additional use cases and migration experiences to enhance the current set of rulesets. If you have valuable insights or experiences to share, we encourage you to join the Migration-experience User Group. To find out more about getting involved, please click here.

                  \ No newline at end of file +

                  Click here to watch the video for part 3 in action - Refractor and Deploy to K8s

                  Conclusion

                  Get involved in the Konveyor Community

                  The Konveyor project is actively seeking additional use cases and migration experiences to enhance the current set of rulesets. If you have valuable insights or experiences to share, we encourage you to join the Migration-experience User Group. To find out more about getting involved, please click here.

                  \ No newline at end of file diff --git a/blog/one-year-cncf-sandbox-konveyor-reflective-journey/index.html b/blog/one-year-cncf-sandbox-konveyor-reflective-journey/index.html new file mode 100644 index 00000000..2b5a1434 --- /dev/null +++ b/blog/one-year-cncf-sandbox-konveyor-reflective-journey/index.html @@ -0,0 +1,55 @@ +One Year in the CNCF Sandbox- Konveyor's Reflective Journey | Konveyor Community
                  Konveyor is now a Cloud Native Computing Foundation (CNCF) Sandbox project

                  Sep 21, 2023

                  One Year in the CNCF Sandbox- Konveyor's Reflective Journey

                  Tags:

                  Author: Savitha Raghunathan

                  It has been an exceptional year for Konveyor since its admission into the CNCF in July 2022. Since then, the project has undergone a series of transformative changes and remarkable achievements, guided by a newly updated charter that has refocused Konveyor’s mission towards refactoring and replatforming legacy applications. In this post, we invite you to join us on a journey down memory lane as we celebrate the numerous milestones, both big and small, that our dedicated contributors have accomplished over the past year.

                  In the initial months following Konveyor’s acceptance into the CNCF sandbox, considerable effort was invested in establishing essential contributor documentation, forming a steering committee, and embracing best practices for repository management. We extend our heartfelt gratitude to Josh Berkus and Lenka Bočincová from Red Hat OSPO for their invaluable guidance in onboarding Konveyor into the CNCF. CNCF TAG-Contribex has developed project templates that played a vital role in expediting our onboarding process. These templates encompassed everything from code of conduct to vulnerability management, demonstrating the thoughtful process of the TAG-Contribex team in helping project maintainers onboard easily.

                  With the revised charter, Konveyor’s mission has now evolved to “Accelerate the adoption of Kubernetes by assisting organizations in modernizing their legacy applications with Kubernetes and cloud-native technologies in a secure and predictable manner at scale, delivering value at every stage of the adoption journey.” The project’s future vision is encapsulated in the Unified Experience, which serves as our guiding light for all development efforts. The evolution of Konveyor’s roadmap is clearly evident, commencing with the initial emphasis on surfacing information in its 0.1 release. Subsequent release 0.2, extended this focus to enable the planning of work in the form of migration waves, culminating in a significant milestone in 0.3 - a comprehensive rewrite of the analysis engine. This rewrite is built upon the Language Server Protocol, laying the foundation for multi-language analysis capabilities. Currently, this feature supports Java and Go, with active development underway to extend this support to .NET/C#.

                  We are excited to share that Claranet is the latest contributor and community supporter of Konveyor. Their collaboration has been invaluable, as they have shared their extensive migration experience and knowledge, greatly enhancing the assessment of applications within the project. Claranet has introduced the Konveyor Add-On for Amazon EKS Blueprints, and they have also packaged Konveyor for effortless deployment on AWS, simplifying the onboarding process for organizations embarking on their modernization journey. If you have migration experiences to share, we encourage you to join the Konveyor community meetings.

                  For the stats enthusiasts among us, here are some interesting metrics from the past year:

                  • New Contributors: 38
                  • Pull Requests: 2.44K
                  • Issues Addressed: 903
                  • Total Contributions: 21.7K
                  • Commits: 3.9K

                  As we reflect on the remarkable progress achieved over the past year, we want to express our heartfelt gratitude to our contributors and supporters. It is your dedication and support that have made these achievements possible. We look forward to another year of growth, collaboration, and success in the Konveyor project.

                  \ No newline at end of file diff --git a/blog/reflecting-on-large-scale-cloud-native-modernizations-at-kubecon-23/index.html b/blog/reflecting-on-large-scale-cloud-native-modernizations-at-kubecon-23/index.html index bd5a039e..00e41008 100644 --- a/blog/reflecting-on-large-scale-cloud-native-modernizations-at-kubecon-23/index.html +++ b/blog/reflecting-on-large-scale-cloud-native-modernizations-at-kubecon-23/index.html @@ -104,4 +104,4 @@ can offer such as scalability, reliability, and cost efficiency.

                  Don’t reinvent the wheel

                  When talking about migrations, patterns are critical from the applications to the methodologies and tooling. We have seen cases where companies are trying to reinvent the wheel, leading to a significant spend of $$$, resources, and sometimes to the right solution for them. We recommend researching and getting involved with community and modernization experts, -who can help you find the best path quickly and save costs for your organization.

                  https://youtu.be/k-Pvzg9eosQ

                  Help improve the Konveyor project by sharing your application modernization problems and solutions here.

                  Your learnings will be used to improve the Konveyor project and help ease others modernize.

                  \ No newline at end of file +who can help you find the best path quickly and save costs for your organization.

                  https://youtu.be/k-Pvzg9eosQ

                  Help improve the Konveyor project by sharing your application modernization problems and solutions here.

                  Your learnings will be used to improve the Konveyor project and help ease others modernize.

                  \ No newline at end of file diff --git a/blog/release-announcement-0-2-1/index.html b/blog/release-announcement-0-2-1/index.html index ad28f6e2..01388849 100644 --- a/blog/release-announcement-0-2-1/index.html +++ b/blog/release-announcement-0-2-1/index.html @@ -52,4 +52,4 @@ } } }) -
                  Konveyor is now a Cloud Native Computing Foundation (CNCF) Sandbox project

                  Jul 6, 2023

                  Konveyor v0.2.1 Release Announcement

                  Tags:

                  We are thrilled to announce the release of Konveyor 0.2.1! This release supports various features, like migration waves, integration with Jira, and other valuable minor updates.

                  Key Highlights of Konveyor 0.2.1:

                  • Migration waves
                  • Jira Integration
                  • Minor improvements

                  Migration Waves:

                  We are excited to introduce a significant addition to the Konveyor project, aimed at providing enhanced value throughout the migration process. We recognized the need to address the planning aspect required to scale the migration process across entire application portfolio. When dealing with a large-scale portfolio containing hundreds or even thousands of applications, it becomes impractical to execute the migration process in one go. To tackle this challenge, we have introduced the ability for Konveyor to define migration waves, allowing for an iterative and manageable approach. By breaking down the portfolio into waves, we enable a more sophisticated process that in the future we expect will automate the calculation of these waves based on various criteria. This feature empowers users to scale adoption efforts effectively, ensuring a seamless and efficient migration experience.

                  Jira Integration:

                  Jira Integration is a significant development in response to a key concern raised by top managers involved in modernization and migration initiatives. Understanding the overall project progress is crucial, and recognizing that most organizations utilize their task management tools, we have enabled Konveyor to integrate seamlessly with these existing systems to leverage their capabilities. Our approach entails creating tasks or issues within the respective task/issue managers to represent the work associated with each application in the portfolio. Konveyor will then retrieve real-time information about the current status of each application, providing comprehensive project visibility. We have designed a flexible and adaptable integration layer, ensuring that it remains independent of any specific task/issue manager peculiarities on the Konveyor side. Jira is the first implementation, but others could come in the future with other popular issue managers like the ones available in GitHub and GitLab.

                  Minor improvements:

                  These enhancements aim to refine and enhance the overall user experience of our platform. Some of the notable improvements are:

                  • ServiceMonitor for hub metrics: We have introduced ServiceMonitor functionality to capture and monitor hub metrics, providing valuable insights into the performance of your system.

                  • Expose Hub metrics: With this update, we have exposed hub metrics, allowing users to access and utilize metrics for monitoring and analysis purposes.

                  • Make Ingress Creation Optional: This update allows Ingress creation optional, providing flexibility and control over your deployment configurations.

                  • Support for Amazon Load Balancer Ingress controller: Our platform now supports the Amazon Load Balancer Ingress controller, enabling Konveyor to be easily deployed on EKS clusters.

                  • Provide openshift-oauth as an authentication option: As part of our ongoing efforts to enhance authentication capabilities, we now offer openshift-oauth as an additional authentication option, providing more choices to meet your specific requirements.

                  • Make rwx_supported false by default: This feature removes the RWX dependency enabling Konveyor to work without RWX volume by default.

                  These minor improvements reflect our commitment to continuously refining and enhancing our platform to deliver an optimized and user-friendly experience. We value your feedback and encourage you to explore these enhancements as you leverage our latest release. You can install Konveyor 0.2.1 from community operators. If you encounter any issues or have suggestions for features, we encourage you to open an issue here.

                  Happy Modernizing!

                  \ No newline at end of file +
                  Konveyor is now a Cloud Native Computing Foundation (CNCF) Sandbox project

                  Jul 6, 2023

                  Konveyor v0.2.1 Release Announcement

                  Tags:

                  We are thrilled to announce the release of Konveyor 0.2.1! This release supports various features, like migration waves, integration with Jira, and other valuable minor updates.

                  Key Highlights of Konveyor 0.2.1:

                  • Migration waves
                  • Jira Integration
                  • Minor improvements

                  Migration Waves:

                  We are excited to introduce a significant addition to the Konveyor project, aimed at providing enhanced value throughout the migration process. We recognized the need to address the planning aspect required to scale the migration process across entire application portfolio. When dealing with a large-scale portfolio containing hundreds or even thousands of applications, it becomes impractical to execute the migration process in one go. To tackle this challenge, we have introduced the ability for Konveyor to define migration waves, allowing for an iterative and manageable approach. By breaking down the portfolio into waves, we enable a more sophisticated process that in the future we expect will automate the calculation of these waves based on various criteria. This feature empowers users to scale adoption efforts effectively, ensuring a seamless and efficient migration experience.

                  Jira Integration:

                  Jira Integration is a significant development in response to a key concern raised by top managers involved in modernization and migration initiatives. Understanding the overall project progress is crucial, and recognizing that most organizations utilize their task management tools, we have enabled Konveyor to integrate seamlessly with these existing systems to leverage their capabilities. Our approach entails creating tasks or issues within the respective task/issue managers to represent the work associated with each application in the portfolio. Konveyor will then retrieve real-time information about the current status of each application, providing comprehensive project visibility. We have designed a flexible and adaptable integration layer, ensuring that it remains independent of any specific task/issue manager peculiarities on the Konveyor side. Jira is the first implementation, but others could come in the future with other popular issue managers like the ones available in GitHub and GitLab.

                  Minor improvements:

                  These enhancements aim to refine and enhance the overall user experience of our platform. Some of the notable improvements are:

                  • ServiceMonitor for hub metrics: We have introduced ServiceMonitor functionality to capture and monitor hub metrics, providing valuable insights into the performance of your system.

                  • Expose Hub metrics: With this update, we have exposed hub metrics, allowing users to access and utilize metrics for monitoring and analysis purposes.

                  • Make Ingress Creation Optional: This update allows Ingress creation optional, providing flexibility and control over your deployment configurations.

                  • Support for Amazon Load Balancer Ingress controller: Our platform now supports the Amazon Load Balancer Ingress controller, enabling Konveyor to be easily deployed on EKS clusters.

                  • Provide openshift-oauth as an authentication option: As part of our ongoing efforts to enhance authentication capabilities, we now offer openshift-oauth as an additional authentication option, providing more choices to meet your specific requirements.

                  • Make rwx_supported false by default: This feature removes the RWX dependency enabling Konveyor to work without RWX volume by default.

                  These minor improvements reflect our commitment to continuously refining and enhancing our platform to deliver an optimized and user-friendly experience. We value your feedback and encourage you to explore these enhancements as you leverage our latest release. You can install Konveyor 0.2.1 from community operators. If you encounter any issues or have suggestions for features, we encourage you to open an issue here.

                  Happy Modernizing!

                  \ No newline at end of file diff --git a/blog/tackle-2-1-release/index.html b/blog/tackle-2-1-release/index.html index 743e5169..f93715f5 100644 --- a/blog/tackle-2-1-release/index.html +++ b/blog/tackle-2-1-release/index.html @@ -52,4 +52,4 @@ } } }) -
                  Konveyor is now a Cloud Native Computing Foundation (CNCF) Sandbox project

                  Sep 14, 2022

                  Tackle 2.1 release

                  Tags:

                  After the major milestone that Tackle 2.0 represented, the community has continued gathering feedback from the field to further polish the feature set and provide value in the context of modernization, migration and adoption projects. This has led to Tackle 2.1, available now in operatorhub.io, a minor release that has been focused on stabilizing the project and providing a more streamlined user experience, while still delivering some new tooling. The new features include the following:

                  • Integration with the Tackle DiVA project: New report available in the application analysis results providing detailed information about the application data layer, including an extensive inventory of transactions and accessed databases with detailed stack traces for each transaction.
                  • Automated creation of missing entities on CSV import: Tags and Business Services are not required to exist in Tackle prior to the import anymore. This simplifies dealing with large CSV files and the import process overall.
                  • Bulk delete of applications: Applications can now be deleted at bulk in the application inventory. This is especially useful when applications have been imported at bulk by mistake or with some errors.

                  Once again, I would like to congratulate all the different teams involved in the implementation, testing and documentation of this new release of Tackle. We continue building this project together in the community, so any feedback or feature request is definitely welcome. If you feel like something is missing or some feature is not behaving as expected, don’t hesitate to open an issue in the Tackle main repository.

                  Happy modernizing!

                  \ No newline at end of file +
                  Konveyor is now a Cloud Native Computing Foundation (CNCF) Sandbox project

                  Sep 14, 2022

                  Tackle 2.1 release

                  Tags:

                  After the major milestone that Tackle 2.0 represented, the community has continued gathering feedback from the field to further polish the feature set and provide value in the context of modernization, migration and adoption projects. This has led to Tackle 2.1, available now in operatorhub.io, a minor release that has been focused on stabilizing the project and providing a more streamlined user experience, while still delivering some new tooling. The new features include the following:

                  • Integration with the Tackle DiVA project: New report available in the application analysis results providing detailed information about the application data layer, including an extensive inventory of transactions and accessed databases with detailed stack traces for each transaction.
                  • Automated creation of missing entities on CSV import: Tags and Business Services are not required to exist in Tackle prior to the import anymore. This simplifies dealing with large CSV files and the import process overall.
                  • Bulk delete of applications: Applications can now be deleted at bulk in the application inventory. This is especially useful when applications have been imported at bulk by mistake or with some errors.

                  Once again, I would like to congratulate all the different teams involved in the implementation, testing and documentation of this new release of Tackle. We continue building this project together in the community, so any feedback or feature request is definitely welcome. If you feel like something is missing or some feature is not behaving as expected, don’t hesitate to open an issue in the Tackle main repository.

                  Happy modernizing!

                  \ No newline at end of file diff --git a/blog/tackle-2-new-capabilities/index.html b/blog/tackle-2-new-capabilities/index.html index cb26d181..bc195d6e 100644 --- a/blog/tackle-2-new-capabilities/index.html +++ b/blog/tackle-2-new-capabilities/index.html @@ -52,4 +52,4 @@ } } }) -
                  Konveyor is now a Cloud Native Computing Foundation (CNCF) Sandbox project

                  Jun 16, 2022

                  Tackle 2: New capabilities for modernizing applications to leverage Kubernetes

                  Tags:

                  By Ramón Román Nissen

                  We’re thrilled to announce that Tackle 2.0 is now available in operatorhub.io. This new release marks a major milestone for the Tackle project, with a new architecture focused on enhancing performance, scalability and more importantly, extensibility of the tooling available in the Tackle toolkit.

                  This version includes the seamless integration with the analysis capabilities of the Windup project, enabling Tackle to effectively manage, assess and now also analyze applications to have a holistic view at your portfolio when dealing with large scale modernization and Kubernetes adoption initiatives. This is essential to provide key insights that allow Architects leading these massive projects to make informed decisions, thus reducing risks and making the required effort measurable and predictable.

                  The following is a list of the exciting new features included in Tackle 2.0:

                  • Administrator perspective: Dedicated perspective to manage tool-wide configuration, with a similar approach and design to the OpenShift Administrator Perspective.
                  • Enhanced RBAC: Three new differentiated personas with different permissions — Administrator, Architect and Migrator
                  • Integration with repositories: Full integration with source code (Git, Subversion) and binaries (Maven) repositories to automate the retrieval of applications for analysis.
                  • Credentials management: Secure store for multiple credential types (source control, Maven settings files, proxy). Credentials are managed by Administrators and assigned by Architects to applications.
                  • Proxy integration: HTTP and HTTPS proxy configuration can be managed in the Tackle UI.
                  • Analysis module: Full integration with the Windup project to allow the execution of application analysis from the application inventory.
                  • Enhanced analysis modes: Aside from source and binary analysis modes, now Tackle includes the Source + Dependencies mode that parses the POM file available in the source repository to gather dependencies from corporate or public artifact repositories, adding them to the scope of the analysis.
                  • Analysis scope selection: Simplified user experience to configure the analysis scope, with the possibility to force the analysis of known Open Source libraries.
                  • Authless deployment: Tackle can now be optionally deployed without Keycloak, allowing full unauthenticated admin access to the tool. This is especially useful when deploying the tool in resource constrained environments like local instances of Minikube, where only a single user would have access to it.
                  • Seamless upgrades: Tackle lifecycle is now managed by a new operator with Capability Level II, allowing seamless upgrades between GA versions.

                  I would like to take the chance to congratulate the engineering teams involved in the development of this new release of Tackle for making this major leap forward possible. Of course, this has to be extended as well to the UI/UX, QE and Documentation teams that made sure our tool is usable and reliable.

                  Make sure you visit the new official documentation website for Tackle 2 to get started with the tool. We will keep updating the documentation to make sure we cover all the use cases and scenarios in which Tackle can be used. In case you find anything missing, please let us know by creating an issue in the Konveyor documentation repository.

                  Happy modernizing!

                    Bio: Ramón Román is the Product Manager for the Migration Toolkit for Applications within the Modernization and Migration Solutions team in Red Hat. Prior to that, he was part of Red Hat’s Consulting organization, where he worked as an Architect in the field, helping customers succeed in large-scale application migrations and Red Hat OpenShift adoption projects.

                    \ No newline at end of file +
                    Konveyor is now a Cloud Native Computing Foundation (CNCF) Sandbox project

                    Jun 16, 2022

                    Tackle 2: New capabilities for modernizing applications to leverage Kubernetes

                    Tags:

                    By Ramón Román Nissen

                    We’re thrilled to announce that Tackle 2.0 is now available in operatorhub.io. This new release marks a major milestone for the Tackle project, with a new architecture focused on enhancing performance, scalability and more importantly, extensibility of the tooling available in the Tackle toolkit.

                    This version includes the seamless integration with the analysis capabilities of the Windup project, enabling Tackle to effectively manage, assess and now also analyze applications to have a holistic view at your portfolio when dealing with large scale modernization and Kubernetes adoption initiatives. This is essential to provide key insights that allow Architects leading these massive projects to make informed decisions, thus reducing risks and making the required effort measurable and predictable.

                    The following is a list of the exciting new features included in Tackle 2.0:

                    • Administrator perspective: Dedicated perspective to manage tool-wide configuration, with a similar approach and design to the OpenShift Administrator Perspective.
                    • Enhanced RBAC: Three new differentiated personas with different permissions — Administrator, Architect and Migrator
                    • Integration with repositories: Full integration with source code (Git, Subversion) and binaries (Maven) repositories to automate the retrieval of applications for analysis.
                    • Credentials management: Secure store for multiple credential types (source control, Maven settings files, proxy). Credentials are managed by Administrators and assigned by Architects to applications.
                    • Proxy integration: HTTP and HTTPS proxy configuration can be managed in the Tackle UI.
                    • Analysis module: Full integration with the Windup project to allow the execution of application analysis from the application inventory.
                    • Enhanced analysis modes: Aside from source and binary analysis modes, now Tackle includes the Source + Dependencies mode that parses the POM file available in the source repository to gather dependencies from corporate or public artifact repositories, adding them to the scope of the analysis.
                    • Analysis scope selection: Simplified user experience to configure the analysis scope, with the possibility to force the analysis of known Open Source libraries.
                    • Authless deployment: Tackle can now be optionally deployed without Keycloak, allowing full unauthenticated admin access to the tool. This is especially useful when deploying the tool in resource constrained environments like local instances of Minikube, where only a single user would have access to it.
                    • Seamless upgrades: Tackle lifecycle is now managed by a new operator with Capability Level II, allowing seamless upgrades between GA versions.

                    I would like to take the chance to congratulate the engineering teams involved in the development of this new release of Tackle for making this major leap forward possible. Of course, this has to be extended as well to the UI/UX, QE and Documentation teams that made sure our tool is usable and reliable.

                    Make sure you visit the new official documentation website for Tackle 2 to get started with the tool. We will keep updating the documentation to make sure we cover all the use cases and scenarios in which Tackle can be used. In case you find anything missing, please let us know by creating an issue in the Konveyor documentation repository.

                    Happy modernizing!

                      Bio: Ramón Román is the Product Manager for the Migration Toolkit for Applications within the Modernization and Migration Solutions team in Red Hat. Prior to that, he was part of Red Hat’s Consulting organization, where he worked as an Architect in the field, helping customers succeed in large-scale application migrations and Red Hat OpenShift adoption projects.

                      \ No newline at end of file diff --git a/community/index.html b/community/index.html index 06951294..2dd93697 100644 --- a/community/index.html +++ b/community/index.html @@ -58,4 +58,4 @@ false rounded-lg p-4">

                      Subscribe to community updates

                      Stay up-to-speed with all things Konveyor and migrating to Kubernetes by subscribing to our email list.

                      Contribute

                      Ways to contribute:

                      Present to the community

                      Share your experience on migrating to Kubernetes with others. Reach out to get started by sending us an email: konveyorio@gmail.com 

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                      We develop multiple open source tools. We would love for you to take it for a test run and learn more about these tools.

                      Blogs

                      Blogs are open for contribution. Is there a topic you are interested in? Let the organizers know about it by sending us an email: konveyorio@gmail.com 

                      Community Supporters

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                      Read the report

                      The State of Application Modernization Report 2022

                      Learn why enterprises plan to modernize more than half of their existing applications to run on Kubernetes within the next year. And see how these 600 companies will approach the move, along with other key insights, to inform your modernization strategy.

                      Read the report

                      Get Insights On Migrating To Kubernetes

                      Stay up-to-speed with all things Konveyor and migrating to Kubernetes by subscribing to our email list. You'll only hear from us when we have an update worth sharing.

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                      \ No newline at end of file + from-base-200 to-primary-200 dark:from-primary-200 dark:to-intermediate-200 rounded-lg p-4">

                      Blogs

                      Blogs are open for contribution. Is there a topic you are interested in? Let the organizers know about it by sending us an email: konveyorio@gmail.com 

                      Community Supporters

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                      Read the report

                      The State of Application Modernization Report 2022

                      Learn why enterprises plan to modernize more than half of their existing applications to run on Kubernetes within the next year. And see how these 600 companies will approach the move, along with other key insights, to inform your modernization strategy.

                      Read the report

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                      Stay up-to-speed with all things Konveyor and migrating to Kubernetes by subscribing to our email list. You'll only hear from us when we have an update worth sharing.

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                      \ No newline at end of file diff --git a/ecosystem/index.html b/ecosystem/index.html index 78633077..6b10968c 100644 --- a/ecosystem/index.html +++ b/ecosystem/index.html @@ -69,4 +69,4 @@ driven microservices. By analyzing source code, data, and transactional boundaries, this tools helps you discover application domains of interest - and refactor them into microservices.

                      Github Repo

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                      The State of Application Modernization Report 2022

                      Learn why enterprises plan to modernize more than half of their existing applications to run on Kubernetes within the next year. And see how these 600 companies will approach the move, along with other key insights, to inform your modernization strategy.

                      Read the report

                      Get Insights On Migrating To Kubernetes

                      Stay up-to-speed with all things Konveyor and migrating to Kubernetes by subscribing to our email list. You'll only hear from us when we have an update worth sharing.

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                      \ No newline at end of file + and refactor them into microservices.

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                      The State of Application Modernization Report 2022

                      Learn why enterprises plan to modernize more than half of their existing applications to run on Kubernetes within the next year. And see how these 600 companies will approach the move, along with other key insights, to inform your modernization strategy.

                      Read the report

                      Get Insights On Migrating To Kubernetes

                      Stay up-to-speed with all things Konveyor and migrating to Kubernetes by subscribing to our email list. You'll only hear from us when we have an update worth sharing.

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                      \ No newline at end of file diff --git a/index.html b/index.html index 849b3388..40e26a6b 100644 --- a/index.html +++ b/index.html @@ -60,4 +60,4 @@ through automated analysis (pre-packaged or custom rules).
                    1. Fully integrated Konveyor Data Intensive Validity Advisor (DiVA): Analyzes the data layer of applications and detect dependencies to different data stores and distributed transactions. Import target Java application - source files to generate analysis results.
                      2. Get StartedGithub Repo

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                      Read articles on how practitioners bring existing applications to Kubernetes at scale and updates on Konveyor tools.

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                      Read the report

                      The State of Application Modernization Report 2022

                      Learn why enterprises plan to modernize more than half of their existing applications to run on Kubernetes within the next year. And see how these 600 companies will approach the move, along with other key insights, to inform your modernization strategy.

                      Read the report

                      Get Insights On Migrating To Kubernetes

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                      Reflecting on Large-Scale Cloud-Native Modernizations at KubeCon 23

                      \ No newline at end of file + source files to generate analysis results.
                      Get StartedGithub Repo

                      Get involved in the Konveyor Community

                      Meetups

                      Practitioners share migration strategies, lessons learned, and tools used at community live virtual meetups.

                      Watch past meetups

                      Have questions about your migration project or how to use our tools? Ping us on Slack.

                      Join our Slack Channel

                      Use Konveyor tools and submit pull requests to help improve these open source tools.

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                      Read articles on how practitioners bring existing applications to Kubernetes at scale and updates on Konveyor tools.

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                      Read the report

                      The State of Application Modernization Report 2022

                      Learn why enterprises plan to modernize more than half of their existing applications to run on Kubernetes within the next year. And see how these 600 companies will approach the move, along with other key insights, to inform your modernization strategy.

                      Read the report

                      Get Insights On Migrating To Kubernetes

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                      \ No newline at end of file diff --git a/modernization-report/index.html b/modernization-report/index.html index 3ab7974e..1af111b7 100644 --- a/modernization-report/index.html +++ b/modernization-report/index.html @@ -52,5 +52,5 @@ } } }) -
                      Konveyor is now a Cloud Native Computing Foundation (CNCF) Sandbox project

                      State of Application Modernization Report 2022

                      by Gordon Haff

                      Both anecdotes and past surveys tell us that organizations are modernizing their applications. We wanted to dig deeper into the specifics. To do so, Konveyor community contributor Red Hat sponsored a survey of 600 IT decision makers (ITDM), backend developers, and software architects in the US, UK, and English-speaking Asia-Pacific (APAC). We surveyed these respondents, drawn from third-party databases, in October and November of 2021. Their companies had to have an internal app dev team and had to be using or planning to use hybrid cloud or multicloud as well as containers (the overwhelming majority were already using both). Here are some of the things they told us.

                      Modernization is happening quickly

                      Companies plan for more than half of their custom applications to be modernized within the next year.

                      We sought out respondents who were modernizing or planning to modernize their custom apps in some manner, so it’s no surprise that everyone we surveyed is modernizing. What’s perhaps less expected is how quickly they’re planning to modernize. Companies are planning to modernize over half of their custom applications during the next year and over a quarter during the next six months. Only 20% expected the modernization to take more than two years.

                      Does that seem a bit… optimistic? It does. Indeed, as was something of a theme throughout this survey, developers were less confident than their ITDM and architect counterparts that modernization would be either quick or straightforward.

                      The barriers cited by respondents provide additional evidence that modernization projects won’t always be smooth sailing. All regions except the UK said that resistance to change was the top barrier—and in the UK it was still near the top. The fact that this is a cultural challenge far more than a technical one suggests that overcoming such a barrier may be difficult and require senior management buy-in. Other top barriers were related concerns like time constraints, cost and budget constraints, and lack of skilled resources. Skills shortages in particular are a common theme almost across the board when we conduct surveys about important IT initiatives.

                      However, even if you think that a lot of modernization projects are likely to slip out, the data certainly points to an intent to rapidly modernize.

                      There’s no single app modernization strategy

                      Companies intend to replatform, refactor, or repurchase just over half of their custom legacy applications.

                      In considering app modernization strategies, we presented survey respondents with six choices, the widely used six Rs. These are:

                      • Retire: Sunset or decommission applications that are no longer needed
                      • Retain: Leave critical applications as-is until refactoring is required
                      • Rehost: Copy applications to a cloud (whether hosted or on-prem) with minimal changes, i.e. “lift and shift”
                      • Replatform: Use a cloud migration to upgrade operating systems, databases, and other components as needed in order to cloud-enable applications without changing core application code or architecture
                      • Refactor: Re-architect as cloud-native, for example, by containerizing workloads or moving them to a serverless architecture
                      • Repurchase: Move from perpetual licenses to a Software-as-a-Service (SaaS) model

                      That’s quite the range of options and they’re all being used to significant degrees. Retire and retain were each about half as popular than the four other options — which each captured about 20% of the applications being modernized. The overall story is definitely about matching the application modernization strategy to a given workload and company need rather than there being a single dominant approach across companies.

                      We again see developers being more cautious or pessimistic about more aggressive modernization approaches; they were more likely to intend to rehost relative to ITDMs and architects. We sometimes hear about “resume-driven development,” whereby developers supposedly want to gain experience in new technologies, even if doing so increases complexity. However, the developers in our survey were more likely to favor lower risk and lower effort approaches.

                      We also found that refactoring, which is the most involved modernization approach, is almost always a two-step approach. 90% of those who plan to refactor any legacy apps intend to replatform them first.

                      The US is further along than others

                      USUKAPAC
                      Unique Definitions of App ModernizationUsing microservices architecture in the cloudImproving CI/CDImproving CI/CD
                      Unique Reasons for App ModernizationDecrease costsDecrease costsImprove security improve customer experience
                      Unique Barriers
                      • Difficulty determining the right approach
                      • Do no see the value of modernizing
                      		Have not faces any barriersHave not faced any barriers
                      Unique ChallengesDifficulty determining the right approachNo differentiating challengesNo differentiating challenges
                      Unique Success MeasuresDecreased costincreased customer satisfactionImproved security increased customer satisfaction
                      Legacy App StrategyMore likely to retire or retain applicationsMore likely to rehost or repurchase applicationsMost likely to rehost or repurchase applications
                      Unique App Modernization PrioritiesNo differentiating PrioritiesData/analytics/BI applications
                      • Customer-facing applications
                      • Data/analytics/BI applications

                      We don’t generally find striking differences between regions but we do sometimes see more subtle ones that form something of a pattern, as was the case here.

                      In this case, we see the US uniquely defining app modernization as “Using microservices architecture in the cloud” while the other two regions defined it as “Improving CI/CD.” This suggests that the US is further along in app modernization. Having a well-developed CI/CD pipeline is foundational to microservices and other cloud-native technology approaches.

                      We see something similar crop up with respect to barriers and challenges. The UK and APAC haven’t faced any barriers. It’s reasonable to assume that’s because they haven’t gotten far enough into the process yet. By contrast, the US is focused on the “Difficulty determining the right approach,” suggesting that they’re actively figuring out the best way to implement a modernization strategy across their application portfolio.

                      Increasing scalability and reliability trump cost reductions

                      Companies plan to measure success of application modernization base on increased reliability and increased scalability.

                      How are companies going to measure the success of their application modernizations? Decreased costs are one factor. Costs always matter to at least some degree; ask anyone who has ever owned a budget. But increased reliability (especially in the US) and scalability were at the top of the list overall, with security high up as well.

                      This was a question that had significant regional differences. Improving security was a significantly higher-ranked measure in APAC than in other regions and even edged out increased scalability there. APAC was also much more likely to measure increased customer satisfaction—especially relative to the US.

                      AI/ML, data caching, and high performance computing on the upswing

                      More companies expect to have AI/ML software, data caching tools, and high performance computing workloads in place in the next 2 years.

                      While traditional workloads such as web servers, business process applications, and databases are the most common today, they’re not where workload growth is expected to be over the next two years. That would be AI/ML software, data caching (think Redis), and high performance computing, which are expected to grow at least 20% during that period. Analytics falls in between the two groups both in terms of level of usage today and its expected rate of growth.

                      Thus, many new applications and application architectures are likely to be in emerging technology areas which include these high growth workloads. While most of the workloads were fairly consistent across regions, AI/ML in the US (68%) was markedly higher than in the UK (57%) which was higher than in APAC (43%).

                      Is there a public cloud backlash?

                      Companies expect a shift from public cloud toward private cloud deployment 2 years from now, especially in the UK and APAC.

                      The overwhelming majority of the companies we surveyed run at least some of their production applications on a public cloud although a significant number also run on a private cloud—whether on-premise, off-premise, or both.

                      The most striking thing about these numbers though is where they’re headed. The 98% of companies that have at least some production workloads on a public cloud today is expected to drop ten points over the next two years to 88%. This drop is almost entirely attributable to the UK and APAC with the US dropping only one point. In APAC specifically, a full 26% of companies plan to stop using public clouds for production workloads; most of those workloads would appear to be going to off-premise private clouds which have a commensurately large expected increase.

                      What’s going on? Are public clouds falling out of favor?

                      There’s some anecdotal evidence that data egress and a general lack of cost predictability have driven some companies to repatriate certain applications to private clouds. Furthermore, edge computing architectures distribute workloads so as to bring compute resources closer to data and user services. (Although they still often have a cloud component, whether on a public cloud or on-premise.)

                      However, in the US, the percentage of companies with one or more production workloads on a public cloud is expected to stay essentially flat. This suggests that the significant expected shift in the UK and APAC numbers probably isn’t explained by cost and edge computing alone.

                      Based on other surveys we’ve conducted, those other reasons may relate to data privacy, data security, and data sovereignty concerns. It’s not a stretch to imagine that these concerns might be heightened in the UK and APAC, especially in light of the fact that the three large global public cloud providers are all headquartered in the US.

                      The above notwithstanding, however, backlash is probably too strong a term. Rather, with 77% already having a hybrid cloud infrastructure, the results suggest that companies are just increasingly sophisticated in placing workloads on the best kind of infrastructure for the purpose rather than taking more of a one-size-fits-all approach.

                      Slide deck with all findings

                      State of application modernization 2022 from Konveyor Community

                        Gordon Haff is Technology Advocate at Red Hat where he works on emerging technology strategy; writes about tech, trends, and their business impact; and is a frequent speaker at customer and industry events. Among the topics he works on are edge, blockchain, AI, quantum, cloud-native platforms, and next-generation application architectures. His books include From Pots and Vats to Programs and Apps and How Open Source Ate Software. His current podcast is Innovate @ Open. Prior to Red Hat, as an industry analyst, Gordon wrote hundreds of research notes, was frequently quoted in major publications on a wide range of IT topics, and advised clients on product and marketing strategies.

                        What to read next

                        Modernize Petclinic App to Kubernetes Using Konveyor

                        Konveyor aims to surface insights on applications at scale to empower enterprise users to make better-informed decisions related to modernization activities. This tutorial focuses on addressing edge case issues with Hazelcast during Kubernetes migration, emphasizing the benefits of creating custom rules and sharing knowledge to streamline future modernization efforts.

                        Reflecting on Large-Scale Cloud-Native Modernizations at KubeCon 23

                        Migrating large infrastructures from an on-premise, monolithic, traditional IT management approach to a modern cloud-native Kubernetes-based ecosystem is a daunting task. Christopher Nuland (Konveyor Ambassador) led a conversation with Jared Burk and Valentina Rodriguez Sosa, Red Hat; James Bench, Maximus - about the different migrations they have completed and the challenges they experienced.

                        Community Update: Konveyor Refocuses Efforts on Replatforming and Refactoring Use Cases

                        We recently revealed upcoming changes to the Konveyor Project. These adjustments are designed to solve the most important application modernizations problem better and to encourage participation with our community.

                        Tackle 2.1 release

                        New features include a new report that gives details about the application data layer, easier CSV importing, bulk deletion of applications, and a more streamlined user experience.

                        \ No newline at end of file +
                        Konveyor is now a Cloud Native Computing Foundation (CNCF) Sandbox project

                        State of Application Modernization Report 2022

                        by Gordon Haff

                        Both anecdotes and past surveys tell us that organizations are modernizing their applications. We wanted to dig deeper into the specifics. To do so, Konveyor community contributor Red Hat sponsored a survey of 600 IT decision makers (ITDM), backend developers, and software architects in the US, UK, and English-speaking Asia-Pacific (APAC). We surveyed these respondents, drawn from third-party databases, in October and November of 2021. Their companies had to have an internal app dev team and had to be using or planning to use hybrid cloud or multicloud as well as containers (the overwhelming majority were already using both). Here are some of the things they told us.

                        Modernization is happening quickly

                        Companies plan for more than half of their custom applications to be modernized within the next year.

                        We sought out respondents who were modernizing or planning to modernize their custom apps in some manner, so it’s no surprise that everyone we surveyed is modernizing. What’s perhaps less expected is how quickly they’re planning to modernize. Companies are planning to modernize over half of their custom applications during the next year and over a quarter during the next six months. Only 20% expected the modernization to take more than two years.

                        Does that seem a bit… optimistic? It does. Indeed, as was something of a theme throughout this survey, developers were less confident than their ITDM and architect counterparts that modernization would be either quick or straightforward.

                        The barriers cited by respondents provide additional evidence that modernization projects won’t always be smooth sailing. All regions except the UK said that resistance to change was the top barrier—and in the UK it was still near the top. The fact that this is a cultural challenge far more than a technical one suggests that overcoming such a barrier may be difficult and require senior management buy-in. Other top barriers were related concerns like time constraints, cost and budget constraints, and lack of skilled resources. Skills shortages in particular are a common theme almost across the board when we conduct surveys about important IT initiatives.

                        However, even if you think that a lot of modernization projects are likely to slip out, the data certainly points to an intent to rapidly modernize.

                        There’s no single app modernization strategy

                        Companies intend to replatform, refactor, or repurchase just over half of their custom legacy applications.

                        In considering app modernization strategies, we presented survey respondents with six choices, the widely used six Rs. These are:

                        • Retire: Sunset or decommission applications that are no longer needed
                        • Retain: Leave critical applications as-is until refactoring is required
                        • Rehost: Copy applications to a cloud (whether hosted or on-prem) with minimal changes, i.e. “lift and shift”
                        • Replatform: Use a cloud migration to upgrade operating systems, databases, and other components as needed in order to cloud-enable applications without changing core application code or architecture
                        • Refactor: Re-architect as cloud-native, for example, by containerizing workloads or moving them to a serverless architecture
                        • Repurchase: Move from perpetual licenses to a Software-as-a-Service (SaaS) model

                        That’s quite the range of options and they’re all being used to significant degrees. Retire and retain were each about half as popular than the four other options — which each captured about 20% of the applications being modernized. The overall story is definitely about matching the application modernization strategy to a given workload and company need rather than there being a single dominant approach across companies.

                        We again see developers being more cautious or pessimistic about more aggressive modernization approaches; they were more likely to intend to rehost relative to ITDMs and architects. We sometimes hear about “resume-driven development,” whereby developers supposedly want to gain experience in new technologies, even if doing so increases complexity. However, the developers in our survey were more likely to favor lower risk and lower effort approaches.

                        We also found that refactoring, which is the most involved modernization approach, is almost always a two-step approach. 90% of those who plan to refactor any legacy apps intend to replatform them first.

                        The US is further along than others

                        USUKAPAC
                        Unique Definitions of App ModernizationUsing microservices architecture in the cloudImproving CI/CDImproving CI/CD
                        Unique Reasons for App ModernizationDecrease costsDecrease costsImprove security improve customer experience
                        Unique Barriers
                        • Difficulty determining the right approach
                        • Do no see the value of modernizing
                        		Have not faces any barriersHave not faced any barriers
                        Unique ChallengesDifficulty determining the right approachNo differentiating challengesNo differentiating challenges
                        Unique Success MeasuresDecreased costincreased customer satisfactionImproved security increased customer satisfaction
                        Legacy App StrategyMore likely to retire or retain applicationsMore likely to rehost or repurchase applicationsMost likely to rehost or repurchase applications
                        Unique App Modernization PrioritiesNo differentiating PrioritiesData/analytics/BI applications
                        • Customer-facing applications
                        • Data/analytics/BI applications

                        We don’t generally find striking differences between regions but we do sometimes see more subtle ones that form something of a pattern, as was the case here.

                        In this case, we see the US uniquely defining app modernization as “Using microservices architecture in the cloud” while the other two regions defined it as “Improving CI/CD.” This suggests that the US is further along in app modernization. Having a well-developed CI/CD pipeline is foundational to microservices and other cloud-native technology approaches.

                        We see something similar crop up with respect to barriers and challenges. The UK and APAC haven’t faced any barriers. It’s reasonable to assume that’s because they haven’t gotten far enough into the process yet. By contrast, the US is focused on the “Difficulty determining the right approach,” suggesting that they’re actively figuring out the best way to implement a modernization strategy across their application portfolio.

                        Increasing scalability and reliability trump cost reductions

                        Companies plan to measure success of application modernization base on increased reliability and increased scalability.

                        How are companies going to measure the success of their application modernizations? Decreased costs are one factor. Costs always matter to at least some degree; ask anyone who has ever owned a budget. But increased reliability (especially in the US) and scalability were at the top of the list overall, with security high up as well.

                        This was a question that had significant regional differences. Improving security was a significantly higher-ranked measure in APAC than in other regions and even edged out increased scalability there. APAC was also much more likely to measure increased customer satisfaction—especially relative to the US.

                        AI/ML, data caching, and high performance computing on the upswing

                        More companies expect to have AI/ML software, data caching tools, and high performance computing workloads in place in the next 2 years.

                        While traditional workloads such as web servers, business process applications, and databases are the most common today, they’re not where workload growth is expected to be over the next two years. That would be AI/ML software, data caching (think Redis), and high performance computing, which are expected to grow at least 20% during that period. Analytics falls in between the two groups both in terms of level of usage today and its expected rate of growth.

                        Thus, many new applications and application architectures are likely to be in emerging technology areas which include these high growth workloads. While most of the workloads were fairly consistent across regions, AI/ML in the US (68%) was markedly higher than in the UK (57%) which was higher than in APAC (43%).

                        Is there a public cloud backlash?

                        Companies expect a shift from public cloud toward private cloud deployment 2 years from now, especially in the UK and APAC.

                        The overwhelming majority of the companies we surveyed run at least some of their production applications on a public cloud although a significant number also run on a private cloud—whether on-premise, off-premise, or both.

                        The most striking thing about these numbers though is where they’re headed. The 98% of companies that have at least some production workloads on a public cloud today is expected to drop ten points over the next two years to 88%. This drop is almost entirely attributable to the UK and APAC with the US dropping only one point. In APAC specifically, a full 26% of companies plan to stop using public clouds for production workloads; most of those workloads would appear to be going to off-premise private clouds which have a commensurately large expected increase.

                        What’s going on? Are public clouds falling out of favor?

                        There’s some anecdotal evidence that data egress and a general lack of cost predictability have driven some companies to repatriate certain applications to private clouds. Furthermore, edge computing architectures distribute workloads so as to bring compute resources closer to data and user services. (Although they still often have a cloud component, whether on a public cloud or on-premise.)

                        However, in the US, the percentage of companies with one or more production workloads on a public cloud is expected to stay essentially flat. This suggests that the significant expected shift in the UK and APAC numbers probably isn’t explained by cost and edge computing alone.

                        Based on other surveys we’ve conducted, those other reasons may relate to data privacy, data security, and data sovereignty concerns. It’s not a stretch to imagine that these concerns might be heightened in the UK and APAC, especially in light of the fact that the three large global public cloud providers are all headquartered in the US.

                        The above notwithstanding, however, backlash is probably too strong a term. Rather, with 77% already having a hybrid cloud infrastructure, the results suggest that companies are just increasingly sophisticated in placing workloads on the best kind of infrastructure for the purpose rather than taking more of a one-size-fits-all approach.

                        Slide deck with all findings

                        State of application modernization 2022 from Konveyor Community

                          Gordon Haff is Technology Advocate at Red Hat where he works on emerging technology strategy; writes about tech, trends, and their business impact; and is a frequent speaker at customer and industry events. Among the topics he works on are edge, blockchain, AI, quantum, cloud-native platforms, and next-generation application architectures. His books include From Pots and Vats to Programs and Apps and How Open Source Ate Software. His current podcast is Innovate @ Open. Prior to Red Hat, as an industry analyst, Gordon wrote hundreds of research notes, was frequently quoted in major publications on a wide range of IT topics, and advised clients on product and marketing strategies.

                          What to read next

                          One Year in the CNCF Sandbox- Konveyor's Reflective Journey

                          It has been an exceptional year for Konveyor since its admission into the CNCF in July 2022. Since then, the project has undergone a series of transformative changes and remarkable achievements, guided by a newly updated charter that has refocused Konveyor's mission towards refactoring and replatforming legacy applications. In this post, we invite you to join us on a journey down memory lane as we celebrate the numerous milestones, both big and small, that our dedicated contributors have accomplished over the past year.

                          Modernize Petclinic App to Kubernetes Using Konveyor

                          Konveyor aims to surface insights on applications at scale to empower enterprise users to make better-informed decisions related to modernization activities. This tutorial focuses on addressing edge case issues with Hazelcast during Kubernetes migration, emphasizing the benefits of creating custom rules and sharing knowledge to streamline future modernization efforts.

                          Reflecting on Large-Scale Cloud-Native Modernizations at KubeCon 23

                          Migrating large infrastructures from an on-premise, monolithic, traditional IT management approach to a modern cloud-native Kubernetes-based ecosystem is a daunting task. Christopher Nuland (Konveyor Ambassador) led a conversation with Jared Burk and Valentina Rodriguez Sosa, Red Hat; James Bench, Maximus + about the different migrations they have completed and the challenges they experienced.

                          Community Update: Konveyor Refocuses Efforts on Replatforming and Refactoring Use Cases

                          We recently revealed upcoming changes to the Konveyor Project. These adjustments are designed to solve the most important application modernizations problem better and to encourage participation with our community.

                          Tackle 2.1 release

                          New features include a new report that gives details about the application data layer, easier CSV importing, bulk deletion of applications, and a more streamlined user experience.

                          \ No newline at end of file diff --git a/page-data/blog/2/page-data.json b/page-data/blog/2/page-data.json index 2688df93..15675449 100644 --- a/page-data/blog/2/page-data.json +++ b/page-data/blog/2/page-data.json @@ -1 +1 @@ -{"componentChunkName":"component---src-templates-blog-js","path":"/blog/2","result":{"data":{"latestPosts":{"nodes":[{"id":"34b76663-da5d-5d41-80e7-163c298238cd","slug":"tackle-2-new-capabilities/","excerpt":"By Ramón Román Nissen We’re thrilled to announce that Tackle 2.0 is now available in operatorhub.io . This new release marks a major…","frontmatter":{"date":"Jun 16, 2022","title":"Tackle 2: New capabilities for modernizing applications to leverage Kubernetes","description":"New management, assessment, and analysis capabilities will help you streamline the modernization of your application portfolio to Kubernetes. 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This project translates existing artifacts to Kubernetes artifacts to speed up the process of being able to run applications on Kubernetes.\"), mdx(\"h2\", {\n \"id\": \"refactoring-applications-with-tackle\",\n \"style\": {\n \"position\": \"relative\"\n }\n }, \"Refactoring applications with Tackle\", mdx(\"a\", {\n parentName: \"h2\",\n \"href\": \"#refactoring-applications-with-tackle\",\n \"aria-label\": \"refactoring applications with tackle permalink\",\n \"className\": \"anchor after\"\n }, mdx(\"svg\", {\n parentName: \"a\",\n \"aria-hidden\": \"true\",\n \"version\": \"1.1\",\n \"viewBox\": \"0 0 16 16\"\n }, mdx(\"path\", {\n parentName: \"svg\",\n \"fill\": \"currentColor\",\n \"fillRule\": \"evenodd\",\n \"d\": \"M4 9h1v1H4c-1.5 0-3-1.69-3-3.5S2.55 3 4 3h4c1.45 0 3 1.69 3 3.5 0 1.41-.91 2.72-2 3.25V8.59c.58-.45 1-1.27 1-2.09C10 5.22 8.98 4 8 4H4c-.98 0-2 1.22-2 2.5S3 9 4 9zm9-3h-1v1h1c1 0 2 1.22 2 2.5S13.98 12 13 12H9c-.98 0-2-1.22-2-2.5 0-.83.42-1.64 1-2.09V6.25c-1.09.53-2 1.84-2 3.25C6 11.31 7.55 13 9 13h4c1.45 0 3-1.69 3-3.5S14.5 6 13 6z\"\n })))), mdx(\"p\", null, \"Refactoring (17%) is often viewed as the most challenging application modernization strategy but it\\u2019s the one with the most long-term impact. Refactoring involves re-architecting as cloud-native, for example, by containerizing workloads, transforming a monolith to microservices, or moving functions to a serverless architecture.\"), mdx(\"p\", null, \"While \", mdx(\"strong\", {\n parentName: \"p\"\n }, \"Tackle\"), \" is not a full refactoring tool, it provides a series of interrelated tools that allow users to assess, analyze, and ultimately move their applications onto a Kubernetes orchestrated platform.\"), mdx(\"hr\", null), mdx(\"p\", null, \"As you can see, organizations are taking a thoughtful approach to app migration and there\\u2019s no single right path. This data supports the Konveyor community\\u2019s approach of providing a toolbox, rather than just a singular tool, that can support transitioning applications however it is happening.\"));\n}\n;\nMDXContent.isMDXComponent = true;","frontmatter":{"date":"Mar 9, 2022","title":"Application Modernization Report Shows Need For Kubernetes-specific Migration Tooling","description":"In MTC 1.4.0, a new feature called Direct Migration is available that will yield significant time savings for most customers migrating persistent volumes and/or internal images.","tags":["Kubernetes"],"image":{"childImageSharp":{"gatsbyImageData":{"layout":"fullWidth","backgroundColor":"#282868","images":{"fallback":{"src":"/static/537937dcba2ec12bf22f3164555e57fc/60e49/report-22-banner.jpg","srcSet":"/static/537937dcba2ec12bf22f3164555e57fc/ffae8/report-22-banner.jpg 750w,\n/static/537937dcba2ec12bf22f3164555e57fc/271eb/report-22-banner.jpg 1080w,\n/static/537937dcba2ec12bf22f3164555e57fc/ef7f4/report-22-banner.jpg 1366w,\n/static/537937dcba2ec12bf22f3164555e57fc/60e49/report-22-banner.jpg 1764w","sizes":"100vw"},"sources":[{"srcSet":"/static/537937dcba2ec12bf22f3164555e57fc/5f165/report-22-banner.webp 750w,\n/static/537937dcba2ec12bf22f3164555e57fc/29464/report-22-banner.webp 1080w,\n/static/537937dcba2ec12bf22f3164555e57fc/d62df/report-22-banner.webp 1366w,\n/static/537937dcba2ec12bf22f3164555e57fc/4e998/report-22-banner.webp 1764w","type":"image/webp","sizes":"100vw"}]},"width":1,"height":0.45068027210884354}}}}}},"pageContext":{"id":"12cda7c0-1878-5c73-9ed1-b19f21c3c3b5","slug":"application-modernization-report/","__params":{"slug":"application-modernization-report"}}},"staticQueryHashes":["1129262270","1953051027","2744294623","287575728","3649515864","3663114508","4063661203"]} \ No newline at end of file +{"componentChunkName":"component---src-pages-blog-mdx-slug-js","path":"/blog/application-modernization-report/","result":{"data":{"mdx":{"id":"12cda7c0-1878-5c73-9ed1-b19f21c3c3b5","slug":"application-modernization-report/","body":"var _excluded = [\"components\"];\nfunction _extends() { _extends = Object.assign ? Object.assign.bind() : function (target) { for (var i = 1; i < arguments.length; i++) { var source = arguments[i]; for (var key in source) { if (Object.prototype.hasOwnProperty.call(source, key)) { target[key] = source[key]; } } } return target; }; return _extends.apply(this, arguments); }\nfunction _objectWithoutProperties(source, excluded) { if (source == null) return {}; var target = _objectWithoutPropertiesLoose(source, excluded); var key, i; if (Object.getOwnPropertySymbols) { var sourceSymbolKeys = Object.getOwnPropertySymbols(source); for (i = 0; i < sourceSymbolKeys.length; i++) { key = sourceSymbolKeys[i]; if (excluded.indexOf(key) >= 0) continue; if (!Object.prototype.propertyIsEnumerable.call(source, key)) continue; target[key] = source[key]; } } return target; }\nfunction _objectWithoutPropertiesLoose(source, excluded) { if (source == null) return {}; var target = {}; var sourceKeys = Object.keys(source); var key, i; for (i = 0; i < sourceKeys.length; i++) { key = sourceKeys[i]; if (excluded.indexOf(key) >= 0) continue; target[key] = source[key]; } return target; }\n/* @jsxRuntime classic */\n/* @jsx mdx */\n\nvar _frontmatter = {\n \"author\": \"ghaff\",\n \"date\": \"2022-03-09T07:00:00.000Z\",\n \"description\": \"In MTC 1.4.0, a new feature called Direct Migration is available that will yield significant time savings for most customers migrating persistent volumes and/or internal images.\",\n \"featured\": false,\n \"image\": \"report-22-banner.jpg\",\n \"tags\": [\"Kubernetes\"],\n \"title\": \"Application Modernization Report Shows Need For Kubernetes-specific Migration Tooling\"\n};\nvar layoutProps = {\n _frontmatter: _frontmatter\n};\nvar MDXLayout = \"wrapper\";\nreturn function MDXContent(_ref) {\n var components = _ref.components,\n props = _objectWithoutProperties(_ref, _excluded);\n return mdx(MDXLayout, _extends({}, layoutProps, props, {\n components: components,\n mdxType: \"MDXLayout\"\n }), mdx(\"p\", null, \"Konveyor is a community of people passionate about helping others modernize and migrate their applications to the hybrid cloud by building tools, identifying patterns, and providing advice on how to break down monoliths, adopt containers, and embrace Kubernetes. To do so the Konveyor community is currently working on five projects to help users rehost, replatform, and refactor their applications to Kubernetes.\"), mdx(\"p\", null, \"While conversations with users and data from various sources gave us some visibility into how migrations were taking place, we wanted to inform our priorities with recent detailed data. To do so, Red Hat, a Konveyor community contributor, sponsored a survey of 600 IT decision makers, backend developers, and software architects in the US, UK, and English-speaking Asia-Pacific (APAC) to better understand the application modernization landscape.\"), mdx(\"p\", null, \"Here are some of the findings that relate to Konveyor and application modernization:\"), mdx(\"h2\", {\n \"id\": \"application-modernization-is-happening-now\",\n \"style\": {\n \"position\": \"relative\"\n }\n }, \"Application modernization is happening now\", mdx(\"a\", {\n parentName: \"h2\",\n \"href\": \"#application-modernization-is-happening-now\",\n \"aria-label\": \"application modernization is happening now permalink\",\n \"className\": \"anchor after\"\n }, mdx(\"svg\", {\n parentName: \"a\",\n \"aria-hidden\": \"true\",\n \"version\": \"1.1\",\n \"viewBox\": \"0 0 16 16\"\n }, mdx(\"path\", {\n parentName: \"svg\",\n \"fill\": \"currentColor\",\n \"fillRule\": \"evenodd\",\n \"d\": \"M4 9h1v1H4c-1.5 0-3-1.69-3-3.5S2.55 3 4 3h4c1.45 0 3 1.69 3 3.5 0 1.41-.91 2.72-2 3.25V8.59c.58-.45 1-1.27 1-2.09C10 5.22 8.98 4 8 4H4c-.98 0-2 1.22-2 2.5S3 9 4 9zm9-3h-1v1h1c1 0 2 1.22 2 2.5S13.98 12 13 12H9c-.98 0-2-1.22-2-2.5 0-.83.42-1.64 1-2.09V6.25c-1.09.53-2 1.84-2 3.25C6 11.31 7.55 13 9 13h4c1.45 0 3-1.69 3-3.5S14.5 6 13 6z\"\n })))), mdx(\"p\", null, \"It\\u2019s clear that there is urgency to roll out migration tooling. Among those we surveyed, those who were migrating or planning to, we found that they plan to modernize over half of their custom applications during the next year and over a quarter during the next six months. Only 20% expected the modernization to take more than two years. It\\u2019s clear this is happening right now.\"), mdx(\"p\", null, \"That said, it\\u2019s not all smooth sailing and this doesn\\u2019t happen overnight. While some regions haven\\u2019t progressed far enough in their application modernization journey to experience serious barriers, others (notably the US) report that choosing a straightforward approach can be challenging. Organizations have many options to choose from and each option presents varying levels of complexity.\"), mdx(\"p\", null, mdx(\"img\", {\n parentName: \"p\",\n \"src\": \"/25c8a63ba171fdd05954dbf68178f5d3/modernization-plan.svg\",\n \"alt\": \"Companies plan for more than half of their custom applications to be modernized within the next year.\"\n })), mdx(\"h2\", {\n \"id\": \"motivators-for-modernizing-existing-applications-to-kubernetes\",\n \"style\": {\n \"position\": \"relative\"\n }\n }, \"Motivators for modernizing existing applications to Kubernetes\", mdx(\"a\", {\n parentName: \"h2\",\n \"href\": \"#motivators-for-modernizing-existing-applications-to-kubernetes\",\n \"aria-label\": \"motivators for modernizing existing applications to kubernetes permalink\",\n \"className\": \"anchor after\"\n }, mdx(\"svg\", {\n parentName: \"a\",\n \"aria-hidden\": \"true\",\n \"version\": \"1.1\",\n \"viewBox\": \"0 0 16 16\"\n }, mdx(\"path\", {\n parentName: \"svg\",\n \"fill\": \"currentColor\",\n \"fillRule\": \"evenodd\",\n \"d\": \"M4 9h1v1H4c-1.5 0-3-1.69-3-3.5S2.55 3 4 3h4c1.45 0 3 1.69 3 3.5 0 1.41-.91 2.72-2 3.25V8.59c.58-.45 1-1.27 1-2.09C10 5.22 8.98 4 8 4H4c-.98 0-2 1.22-2 2.5S3 9 4 9zm9-3h-1v1h1c1 0 2 1.22 2 2.5S13.98 12 13 12H9c-.98 0-2-1.22-2-2.5 0-.83.42-1.64 1-2.09V6.25c-1.09.53-2 1.84-2 3.25C6 11.31 7.55 13 9 13h4c1.45 0 3-1.69 3-3.5S14.5 6 13 6z\"\n })))), mdx(\"p\", null, \"The survey tells us modernization is mostly being driven by the need for reliability, scalability and security. Decreasing costs were also on the list but, as we frequently see in other surveys about technology adoption or change, it\\u2019s not the driving factor.\"), mdx(\"p\", null, mdx(\"img\", {\n parentName: \"p\",\n \"src\": \"/d4950fe01bd80a80a66802c5e7a4e20a/increase-scalability.svg\",\n \"alt\": \"Most companies decide to modernize their applications to increase scalability or reliability. Companies in APAC also seek to improve security and customer experience, while those in the US and UK want to decrease costs.\"\n })), mdx(\"p\", null, \"Konveyor\\u2019s tool suite can be used to help realize organization\\u2019s migration plans.\"), mdx(\"p\", null, mdx(\"img\", {\n parentName: \"p\",\n \"src\": \"/4492bd46f7e3ec1fbfbfa708bfdb9cf9/map-to-konveyor.svg\",\n \"alt\": \"How migration strategies companies intend to use based on this survey map to the Konveyor Tool Suite.\"\n })), mdx(\"p\", null, \"The Konveyor tool suite maps closely to the migration strategies companies intend to use based on this survey: rehosting, replatforming, and refactoring.\"), mdx(\"p\", null, mdx(\"img\", {\n parentName: \"p\",\n \"src\": \"/6e40a8a0031cbecc427b0d57fd55157b/replatform-plan.svg\",\n \"alt\": \"Companies intend to replatform, refactor, or repurchase just over half of their custom legacy applications.\"\n })), mdx(\"h2\", {\n \"id\": \"rehost-applications-to-cloud-with-forklift-and-crane\",\n \"style\": {\n \"position\": \"relative\"\n }\n }, \"Rehost applications to cloud with Forklift and Crane\", mdx(\"a\", {\n parentName: \"h2\",\n \"href\": \"#rehost-applications-to-cloud-with-forklift-and-crane\",\n \"aria-label\": \"rehost applications to cloud with forklift and crane permalink\",\n \"className\": \"anchor after\"\n }, mdx(\"svg\", {\n parentName: \"a\",\n \"aria-hidden\": \"true\",\n \"version\": \"1.1\",\n \"viewBox\": \"0 0 16 16\"\n }, mdx(\"path\", {\n parentName: \"svg\",\n \"fill\": \"currentColor\",\n \"fillRule\": \"evenodd\",\n \"d\": \"M4 9h1v1H4c-1.5 0-3-1.69-3-3.5S2.55 3 4 3h4c1.45 0 3 1.69 3 3.5 0 1.41-.91 2.72-2 3.25V8.59c.58-.45 1-1.27 1-2.09C10 5.22 8.98 4 8 4H4c-.98 0-2 1.22-2 2.5S3 9 4 9zm9-3h-1v1h1c1 0 2 1.22 2 2.5S13.98 12 13 12H9c-.98 0-2-1.22-2-2.5 0-.83.42-1.64 1-2.09V6.25c-1.09.53-2 1.84-2 3.25C6 11.31 7.55 13 9 13h4c1.45 0 3-1.69 3-3.5S14.5 6 13 6z\"\n })))), mdx(\"p\", null, \"Rehosting (20% of total) involves copying applications to a cloud (whether hosted or on-prem) with minimal changes, i.e. \\u201Clift and shift.\\u201D This will be familiar to anyone with experience in virtualization early on when bare metal servers were often moved to a virtual machine (VM) for greater efficiency but with little or no changes to the software and with relatively modest operational changes.\"), mdx(\"p\", null, \"While rehosting doesn\\u2019t provide the same depth of benefits as replatforming or refactoring, it\\u2019s the first step in the right direction. Rehosting was the single most common approach\\n\", mdx(\"strong\", {\n parentName: \"p\"\n }, \"Forklift\"), \" and \", mdx(\"strong\", {\n parentName: \"p\"\n }, \"Crane\"), \" are the relevant Konveyor projects here. Forklift is focused on migrating VMs to Kubernetes and provides the ability to migrate multiple VMs to KubeVirt with minimal downtime.\"), mdx(\"p\", null, \"Crane is a rehosting tool that meets a different use case. Crane helps organizations to migrate applications between Kubernetes clusters. There are many times when developers and operations teams want to migrate between older and newer versions of Kubernetes, evacuate a cluster, or migrate to different underlying infrastructure.\"), mdx(\"h2\", {\n \"id\": \"replatforming-applications-with-move2kube\",\n \"style\": {\n \"position\": \"relative\"\n }\n }, \"Replatforming applications with Move2Kube\", mdx(\"a\", {\n parentName: \"h2\",\n \"href\": \"#replatforming-applications-with-move2kube\",\n \"aria-label\": \"replatforming applications with move2kube permalink\",\n \"className\": \"anchor after\"\n }, mdx(\"svg\", {\n parentName: \"a\",\n \"aria-hidden\": \"true\",\n \"version\": \"1.1\",\n \"viewBox\": \"0 0 16 16\"\n }, mdx(\"path\", {\n parentName: \"svg\",\n \"fill\": \"currentColor\",\n \"fillRule\": \"evenodd\",\n \"d\": \"M4 9h1v1H4c-1.5 0-3-1.69-3-3.5S2.55 3 4 3h4c1.45 0 3 1.69 3 3.5 0 1.41-.91 2.72-2 3.25V8.59c.58-.45 1-1.27 1-2.09C10 5.22 8.98 4 8 4H4c-.98 0-2 1.22-2 2.5S3 9 4 9zm9-3h-1v1h1c1 0 2 1.22 2 2.5S13.98 12 13 12H9c-.98 0-2-1.22-2-2.5 0-.83.42-1.64 1-2.09V6.25c-1.09.53-2 1.84-2 3.25C6 11.31 7.55 13 9 13h4c1.45 0 3-1.69 3-3.5S14.5 6 13 6z\"\n })))), mdx(\"p\", null, \"Replatforming (18% of total) is using a cloud migration to upgrade operating systems, databases, and other components as needed in order to cloud-enable applications without changing core application code or architecture. Think of it as \\u201Clift, tinker, and shift.\\u201D\"), mdx(\"p\", null, \"This is effectively an intermediate step between just rehosting and refactoring. In fact, it\\u2019s often a stepping stone; the survey found that 90% of those planning to refactor their apps plan to replatform them first.\"), mdx(\"p\", null, mdx(\"strong\", {\n parentName: \"p\"\n }, \"Move2Kube\"), \" is a Konveyor project that allows customers to replatform their applications to Kubernetes orchestrated platforms. One area where replatforming is taking place is in the consolidation of container orchestration platforms to Kubernetes.\"), mdx(\"p\", null, \"Due to this consolidation, the Move2Kube project was started to focus on accelerating the process of replatforming to Kubernetes from platforms such as Swarm and Cloud Foundry. This project translates existing artifacts to Kubernetes artifacts to speed up the process of being able to run applications on Kubernetes.\"), mdx(\"h2\", {\n \"id\": \"refactoring-applications-with-tackle\",\n \"style\": {\n \"position\": \"relative\"\n }\n }, \"Refactoring applications with Tackle\", mdx(\"a\", {\n parentName: \"h2\",\n \"href\": \"#refactoring-applications-with-tackle\",\n \"aria-label\": \"refactoring applications with tackle permalink\",\n \"className\": \"anchor after\"\n }, mdx(\"svg\", {\n parentName: \"a\",\n \"aria-hidden\": \"true\",\n \"version\": \"1.1\",\n \"viewBox\": \"0 0 16 16\"\n }, mdx(\"path\", {\n parentName: \"svg\",\n \"fill\": \"currentColor\",\n \"fillRule\": \"evenodd\",\n \"d\": \"M4 9h1v1H4c-1.5 0-3-1.69-3-3.5S2.55 3 4 3h4c1.45 0 3 1.69 3 3.5 0 1.41-.91 2.72-2 3.25V8.59c.58-.45 1-1.27 1-2.09C10 5.22 8.98 4 8 4H4c-.98 0-2 1.22-2 2.5S3 9 4 9zm9-3h-1v1h1c1 0 2 1.22 2 2.5S13.98 12 13 12H9c-.98 0-2-1.22-2-2.5 0-.83.42-1.64 1-2.09V6.25c-1.09.53-2 1.84-2 3.25C6 11.31 7.55 13 9 13h4c1.45 0 3-1.69 3-3.5S14.5 6 13 6z\"\n })))), mdx(\"p\", null, \"Refactoring (17%) is often viewed as the most challenging application modernization strategy but it\\u2019s the one with the most long-term impact. Refactoring involves re-architecting as cloud-native, for example, by containerizing workloads, transforming a monolith to microservices, or moving functions to a serverless architecture.\"), mdx(\"p\", null, \"While \", mdx(\"strong\", {\n parentName: \"p\"\n }, \"Tackle\"), \" is not a full refactoring tool, it provides a series of interrelated tools that allow users to assess, analyze, and ultimately move their applications onto a Kubernetes orchestrated platform.\"), mdx(\"hr\", null), mdx(\"p\", null, \"As you can see, organizations are taking a thoughtful approach to app migration and there\\u2019s no single right path. This data supports the Konveyor community\\u2019s approach of providing a toolbox, rather than just a singular tool, that can support transitioning applications however it is happening.\"));\n}\n;\nMDXContent.isMDXComponent = true;","frontmatter":{"date":"Mar 9, 2022","title":"Application Modernization Report Shows Need For Kubernetes-specific Migration Tooling","description":"In MTC 1.4.0, a new feature called Direct Migration is available that will yield significant time savings for most customers migrating persistent volumes and/or internal images.","tags":["Kubernetes"],"image":{"childImageSharp":{"gatsbyImageData":{"layout":"fullWidth","backgroundColor":"#282868","images":{"fallback":{"src":"/static/537937dcba2ec12bf22f3164555e57fc/60e49/report-22-banner.jpg","srcSet":"/static/537937dcba2ec12bf22f3164555e57fc/ffae8/report-22-banner.jpg 750w,\n/static/537937dcba2ec12bf22f3164555e57fc/271eb/report-22-banner.jpg 1080w,\n/static/537937dcba2ec12bf22f3164555e57fc/ef7f4/report-22-banner.jpg 1366w,\n/static/537937dcba2ec12bf22f3164555e57fc/60e49/report-22-banner.jpg 1764w","sizes":"100vw"},"sources":[{"srcSet":"/static/537937dcba2ec12bf22f3164555e57fc/5f165/report-22-banner.webp 750w,\n/static/537937dcba2ec12bf22f3164555e57fc/29464/report-22-banner.webp 1080w,\n/static/537937dcba2ec12bf22f3164555e57fc/d62df/report-22-banner.webp 1366w,\n/static/537937dcba2ec12bf22f3164555e57fc/4e998/report-22-banner.webp 1764w","type":"image/webp","sizes":"100vw"}]},"width":1,"height":0.45068027210884354}}}}}},"pageContext":{"id":"12cda7c0-1878-5c73-9ed1-b19f21c3c3b5","slug":"application-modernization-report/","__params":{"slug":"application-modernization-report"}}},"staticQueryHashes":["1129262270","1953051027","2744294623","287575728","3649515864","3663114508","4063661203"]} \ No newline at end of file diff --git a/page-data/blog/direct-migration/page-data.json b/page-data/blog/direct-migration/page-data.json index 5e1fbc36..8e2b11a4 100644 --- a/page-data/blog/direct-migration/page-data.json +++ b/page-data/blog/direct-migration/page-data.json @@ -1 +1 @@ -{"componentChunkName":"component---src-pages-blog-mdx-slug-js","path":"/blog/direct-migration/","result":{"data":{"mdx":{"id":"54d9c5f1-8225-54fa-930c-37662b36595a","slug":"direct-migration/","body":"var _excluded = [\"components\"];\nfunction _extends() { _extends = Object.assign ? 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Direct Migration enables the migration of persistent volumes and internal images directly from the source cluster to the destination cluster without an intermediary replication repository. This introduces a significant performance enhancement while also providing better error and progress reporting information back to the end-user.\"), mdx(\"p\", null, \"Prior MTC releases only allowed a 2 step backup and restore process when handling images and persistent volumes, which didn\\u2019t take advantage of potential performance savings in the case of a migration with both the source and destination clusters having network connectivity. The prior process leveraged a filesystem copy tool called Restic integrated with Velero. MTC would need to copy PV and Image data twice: once from the source cluster to the replication repository, and a second time from the replication repository to the destination cluster. 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The direct migration feature also grants the user more granular progress and error reporting back in the user interface to make it easier to debug what went wrong with the migration.\"));\n}\n;\nMDXContent.isMDXComponent = true;","frontmatter":{"date":"Feb 24, 2021","title":"Migrating Faster with Direct Migration","description":"In MTC 1.4.0, a new feature called Direct Migration is available that will yield significant time savings for most customers migrating persistent volumes and/or internal images.","tags":["MTC"],"image":{"childImageSharp":{"gatsbyImageData":{"layout":"fullWidth","backgroundColor":"#182828","images":{"fallback":{"src":"/static/4825c880fb32f5e9aeab8ed6a06451f8/fac98/banner.jpg","srcSet":"/static/4825c880fb32f5e9aeab8ed6a06451f8/ffae8/banner.jpg 750w,\n/static/4825c880fb32f5e9aeab8ed6a06451f8/fac98/banner.jpg 900w","sizes":"100vw"},"sources":[{"srcSet":"/static/4825c880fb32f5e9aeab8ed6a06451f8/5f165/banner.webp 750w,\n/static/4825c880fb32f5e9aeab8ed6a06451f8/bf751/banner.webp 900w","type":"image/webp","sizes":"100vw"}]},"width":1,"height":0.44999999999999996}}}}}},"pageContext":{"id":"54d9c5f1-8225-54fa-930c-37662b36595a","slug":"direct-migration/","__params":{"slug":"direct-migration"}}},"staticQueryHashes":["1129262270","1953051027","2744294623","287575728","3649515864","3663114508","4063661203"]} \ No newline at end of file +{"componentChunkName":"component---src-pages-blog-mdx-slug-js","path":"/blog/direct-migration/","result":{"data":{"mdx":{"id":"54d9c5f1-8225-54fa-930c-37662b36595a","slug":"direct-migration/","body":"var _excluded = [\"components\"];\nfunction _extends() { _extends = Object.assign ? Object.assign.bind() : function (target) { for (var i = 1; i < arguments.length; i++) { var source = arguments[i]; for (var key in source) { if (Object.prototype.hasOwnProperty.call(source, key)) { target[key] = source[key]; } } } return target; }; return _extends.apply(this, arguments); }\nfunction _objectWithoutProperties(source, excluded) { if (source == null) return {}; var target = _objectWithoutPropertiesLoose(source, excluded); var key, i; if (Object.getOwnPropertySymbols) { var sourceSymbolKeys = Object.getOwnPropertySymbols(source); for (i = 0; i < sourceSymbolKeys.length; i++) { key = sourceSymbolKeys[i]; if (excluded.indexOf(key) >= 0) continue; if (!Object.prototype.propertyIsEnumerable.call(source, key)) continue; target[key] = source[key]; } } return target; }\nfunction _objectWithoutPropertiesLoose(source, excluded) { if (source == null) return {}; var target = {}; var sourceKeys = Object.keys(source); var key, i; for (i = 0; i < sourceKeys.length; i++) { key = sourceKeys[i]; if (excluded.indexOf(key) >= 0) continue; target[key] = source[key]; } return target; }\n/* @jsxRuntime classic */\n/* @jsx mdx */\n\nvar _frontmatter = {\n \"author\": \"dmurray\",\n \"date\": \"2021-02-24T07:00:00.000Z\",\n \"description\": \"In MTC 1.4.0, a new feature called Direct Migration is available that will yield significant time savings for most customers migrating persistent volumes and/or internal images.\",\n \"featured\": false,\n \"image\": \"banner.jpg\",\n \"tags\": [\"MTC\"],\n \"title\": \"Migrating Faster with Direct Migration\"\n};\nvar layoutProps = {\n _frontmatter: _frontmatter\n};\nvar MDXLayout = \"wrapper\";\nreturn function MDXContent(_ref) {\n var components = _ref.components,\n props = _objectWithoutProperties(_ref, _excluded);\n return mdx(MDXLayout, _extends({}, layoutProps, props, {\n components: components,\n mdxType: \"MDXLayout\"\n }), mdx(\"p\", null, \"In MTC 1.4.0, a new feature called Direct Migration is available that will yield significant time savings for most customers migrating persistent volumes and/or internal images. Direct Migration enables the migration of persistent volumes and internal images directly from the source cluster to the destination cluster without an intermediary replication repository. This introduces a significant performance enhancement while also providing better error and progress reporting information back to the end-user.\"), mdx(\"p\", null, \"Prior MTC releases only allowed a 2 step backup and restore process when handling images and persistent volumes, which didn\\u2019t take advantage of potential performance savings in the case of a migration with both the source and destination clusters having network connectivity. The prior process leveraged a filesystem copy tool called Restic integrated with Velero. MTC would need to copy PV and Image data twice: once from the source cluster to the replication repository, and a second time from the replication repository to the destination cluster. This process yielded flexibility for various environments, yet failed to take advantage of the more common case in a migration of direct network connectivity between clusters.\"), mdx(\"p\", null, \"With Direct Migration in MTC 1.4, we are able to take advantage of any environments that have network connectivity between the clusters involved in the migration by handling the migration of PV data and Image data in a new way. Assuming remote clusters have exposed routes to enable external access to the internal registry, MTC will push internal images directly into the internal registry on the destination cluster from the source cluster. Assuming the clusters can communicate over port 443 via OpenShift routes, MTC will directly migrate Persistent Volume data from a source cluster to a destination cluster using a set of Rsync + Stunnel pods which we will describe more below.\"), mdx(\"h2\", {\n \"id\": \"prerequisites\",\n \"style\": {\n \"position\": \"relative\"\n }\n }, \"Prerequisites\", mdx(\"a\", {\n parentName: \"h2\",\n \"href\": \"#prerequisites\",\n \"aria-label\": \"prerequisites permalink\",\n \"className\": \"anchor after\"\n }, mdx(\"svg\", {\n parentName: \"a\",\n \"aria-hidden\": \"true\",\n \"version\": \"1.1\",\n \"viewBox\": \"0 0 16 16\"\n }, mdx(\"path\", {\n parentName: \"svg\",\n \"fill\": \"currentColor\",\n \"fillRule\": \"evenodd\",\n \"d\": \"M4 9h1v1H4c-1.5 0-3-1.69-3-3.5S2.55 3 4 3h4c1.45 0 3 1.69 3 3.5 0 1.41-.91 2.72-2 3.25V8.59c.58-.45 1-1.27 1-2.09C10 5.22 8.98 4 8 4H4c-.98 0-2 1.22-2 2.5S3 9 4 9zm9-3h-1v1h1c1 0 2 1.22 2 2.5S13.98 12 13 12H9c-.98 0-2-1.22-2-2.5 0-.83.42-1.64 1-2.09V6.25c-1.09.53-2 1.84-2 3.25C6 11.31 7.55 13 9 13h4c1.45 0 3-1.69 3-3.5S14.5 6 13 6z\"\n })))), mdx(\"p\", null, \"As mentioned above for direct image migrations, it is important for remote source and destination clusters internal registries be exposed for external network traffic.\"), mdx(\"ul\", null, mdx(\"li\", {\n parentName: \"ul\"\n }, mdx(\"a\", {\n parentName: \"li\",\n \"href\": \"https://docs.openshift.com/container-platform/4.6/registry/securing-exposing-registry.html\",\n \"target\": \"_blank\",\n \"rel\": \"noopener noreferrer\"\n }, \"expose OCP 4 cluster registry\")), mdx(\"li\", {\n parentName: \"ul\"\n }, mdx(\"a\", {\n parentName: \"li\",\n \"href\": \"https://docs.openshift.com/container-platform/3.11/install_config/registry/securing_and_exposing_registry.html\",\n \"target\": \"_blank\",\n \"rel\": \"noopener noreferrer\"\n }, \"expose OCP 3 cluser registry\"))), mdx(\"p\", null, \"For direct volume migrations, the source and destination clusters must be able to communicate over port 443 via OpenShift routes. MTC will create a route in each namespace to be migrated on the destination cluster and will be migrating the data by establishing an Rsync connection to this route. 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Object.assign.bind() : function (target) { for (var i = 1; i < arguments.length; i++) { var source = arguments[i]; for (var key in source) { if (Object.prototype.hasOwnProperty.call(source, key)) { target[key] = source[key]; } } } return target; }; return _extends.apply(this, arguments); }\nfunction _objectWithoutProperties(source, excluded) { if (source == null) return {}; var target = _objectWithoutPropertiesLoose(source, excluded); var key, i; if (Object.getOwnPropertySymbols) { var sourceSymbolKeys = Object.getOwnPropertySymbols(source); for (i = 0; i < sourceSymbolKeys.length; i++) { key = sourceSymbolKeys[i]; if (excluded.indexOf(key) >= 0) continue; if (!Object.prototype.propertyIsEnumerable.call(source, key)) continue; target[key] = source[key]; } } return target; }\nfunction _objectWithoutPropertiesLoose(source, excluded) { if (source == null) return {}; var target = {}; var sourceKeys = Object.keys(source); var key, i; for (i = 0; i < sourceKeys.length; i++) { key = sourceKeys[i]; if (excluded.indexOf(key) >= 0) continue; target[key] = source[key]; } return target; }\n/* @jsxRuntime classic */\n/* @jsx mdx */\n\nvar _frontmatter = {\n \"author\": \"ospaporta\",\n \"date\": \"2022-07-07T07:00:00.000Z\",\n \"description\": \"we demonstrate that not only is technical debt key to making decisions regarding any specific application, it is also important when attempting to prioritize work between multiple applications.\",\n \"featured\": true,\n \"image\": \"banner.jpg\",\n \"tags\": [\"Metrics\"],\n \"title\": \"A Method to Measure and Manage Technical Debt\"\n};\nvar layoutProps = {\n _frontmatter: _frontmatter\n};\nvar MDXLayout = \"wrapper\";\nreturn function MDXContent(_ref) {\n var components = _ref.components,\n props = _objectWithoutProperties(_ref, _excluded);\n return mdx(MDXLayout, _extends({}, layoutProps, props, {\n components: components,\n mdxType: \"MDXLayout\"\n }), mdx(\"p\", null, \"As a software developer, technical debt is all those little things that you feel are hampering the efficiency of your coding. These are the issues that you (or your manager) choose to handle next time, because of the urgency of the current release. But sometimes, by the time you get to them, they have become so big you do not know where to start solving them. The difficult part is that decisions we make regarding technical debt have to balance between short term and long term implications of accumulating such debt, emphasizing the need to properly assess and address it when planning development cycles.\"), mdx(\"p\", null, \"In their seminal article from 2012\", mdx(\"sup\", {\n parentName: \"p\",\n \"id\": \"fnref-1\"\n }, mdx(\"a\", {\n parentName: \"sup\",\n \"href\": \"#fn-1\",\n \"className\": \"footnote-ref\"\n }, \"1\")), \", Nord et al suggest a metric to measure technical debt, based on dependencies between architectural elements. They use this method to show how an organization should plan development cycles while taking into account the effect the technical debt will have on the overall resources required for each subsequent version.\"), mdx(\"p\", null, \"In this post, we demonstrate that not only is technical debt key to making decisions regarding any specific application, it is also important when attempting to prioritize work between multiple applications. Specifically, modernization work. Moreover, we show a method that can be used to not only compare the performance of different design paths for a single application, but also compare the technical debt levels of multiple applications at an arbitrary point in their development life cycle.\"), mdx(\"p\", null, \"The main idea of the aforementioned article is to provide a way to measure technical debt. It is done using a formula that mainly relies on the dependencies between architectural elements in the given application. 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The dependency graph is a directional graph \", mdx(\"em\", {\n parentName: \"p\"\n }, \"G\"), \" =(\", mdx(\"em\", {\n parentName: \"p\"\n }, \"V\"), \", \", mdx(\"em\", {\n parentName: \"p\"\n }, \"E\"), \") in which the \", mdx(\"em\", {\n parentName: \"p\"\n }, \"V\"), \" = {\", mdx(\"em\", {\n parentName: \"p\"\n }, \"c\"), mdx(\"sub\", null, \"1\"), \", \", mdx(\"em\", {\n parentName: \"p\"\n }, \"c\"), mdx(\"sub\", null, \"2\"), \", \\u2026} is the set of all classes in the application and an edge \", mdx(\"em\", {\n parentName: \"p\"\n }, \"e\"), \" = \\u27E8\", mdx(\"em\", {\n parentName: \"p\"\n }, \"c\"), mdx(\"sub\", null, \"1\"), \", \", mdx(\"em\", {\n parentName: \"p\"\n }, \"c\"), mdx(\"sub\", null, \"2\"), \"\\u27E9 \\u2208 \", mdx(\"em\", {\n parentName: \"p\"\n }, \"E\"), \" exists between two vertices if class \", mdx(\"em\", {\n parentName: \"p\"\n }, \"c\"), mdx(\"sub\", null, \"1\"), \" depends on class \", mdx(\"em\", {\n parentName: \"p\"\n }, \"c\"), mdx(\"sub\", null, \"2\"), \" in the original code. We perform multi-faceted analysis on the graph to eventually come up with a score that describes the technical debt of the application. Here are some of the metrics we extract from the raw graph:\"), mdx(\"ol\", null, mdx(\"li\", {\n parentName: \"ol\"\n }, \"Average/median outdegree of the vertices on the graph\"), mdx(\"li\", {\n parentName: \"ol\"\n }, \"Top N outdegree of any node in the graph.\"), mdx(\"li\", {\n parentName: \"ol\"\n }, \"Longest paths between classes\")), mdx(\"p\", null, \"Using standard clustering algorithms on the graph, we identify communities of classes within the graph and measure additional metrics on them, such as:\"), mdx(\"ol\", null, mdx(\"li\", {\n parentName: \"ol\"\n }, \"Average outdegree of the identified communities\"), mdx(\"li\", {\n parentName: \"ol\"\n }, \"Longest paths between communities\")), mdx(\"p\", null, \"Our hypothesis is that using these generic metrics on the dependency graphs, we can identify architectural issues which represent real technical debt in the original code base. Moreover, by analyzing dependencies on these two levels, class and community, we give a broad interpretation of what an architectural element is in practice, without attempting to formally define it.\"), mdx(\"p\", null, \"To test this method, we created a data set of over fifty applications from a variety of domains (online retail, financial, automotive, etc\\u2026) and extracted the aforementioned metrics from them. We used this data set in two ways. First, we correlated specific instances of high ranking occurrences of outdegrees and long paths with local issues in the code. For example, identifying god classes by their high outdegree\", mdx(\"sup\", {\n parentName: \"p\",\n \"id\": \"fnref-2\"\n }, mdx(\"a\", {\n parentName: \"sup\",\n \"href\": \"#fn-2\",\n \"className\": \"footnote-ref\"\n }, \"2\")), \". This proved efficient and increased our confidence level that this approach is valid in identifying local technical debt issues. The second approach was to try and provide a high level score that can be used not only to identify technical debt in a single application but to also be able to compare technical debt between applications, and to use it to help prioritize which should be addressed and how. To do that we introduced three indexes:\"), mdx(\"ol\", null, mdx(\"li\", {\n parentName: \"ol\"\n }, \"Complexity \\u2014 represents the effort required to add new features into the software.\"), mdx(\"li\", {\n parentName: \"ol\"\n }, \"Risk \\u2014 represents the potential risk that adding new features has on the stability of existing ones.\"), mdx(\"li\", {\n parentName: \"ol\"\n }, \"Overall Debt \\u2014 represents the overall amount of extra work required when attempting to add new features.\")), mdx(\"p\", null, \"We manually analyzed the applications in our data set, also employing the expert knowledge of the architects in charge of actively developing them, and scored each application\\u2019s complexity, risk, and overall debt on a scale of 1-5. We used these benchmarks to train a machine learning model which correlates the values of the extracted metrics with the indexes and normalizes them to a score of 0-100. At this point, we can use this trained model to issue a score per index for any new application we encounter which allows us to analyze entire portfolios of applications, and compare them both to one another and to our pre-calculated benchmark. The following graph depicts a sample of 21 applications demonstrating the relationship between the aforementioned metrics.\"), mdx(\"p\", null, mdx(\"span\", {\n parentName: \"p\",\n \"className\": \"gatsby-resp-image-wrapper\",\n \"style\": {\n \"position\": \"relative\",\n \"display\": \"block\",\n \"marginLeft\": \"auto\",\n \"marginRight\": \"auto\",\n \"maxWidth\": \"971px\"\n }\n }, \"\\n \", mdx(\"a\", {\n parentName: \"span\",\n \"className\": \"gatsby-resp-image-link\",\n \"href\": \"/static/4bf113dc4624bf177c3054ac7bef4935/6e9b1/tech_debt.jpg\",\n \"style\": {\n \"display\": \"block\"\n },\n \"target\": \"_blank\",\n \"rel\": \"noopener\"\n }, \"\\n \", mdx(\"span\", {\n parentName: \"a\",\n \"className\": \"gatsby-resp-image-background-image\",\n \"style\": {\n \"paddingBottom\": \"64%\",\n \"position\": \"relative\",\n \"bottom\": \"0\",\n \"left\": \"0\",\n \"backgroundImage\": \"url('data:image/jpeg;base64,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')\",\n \"backgroundSize\": \"cover\",\n \"display\": \"block\"\n }\n }), \"\\n \", mdx(\"picture\", {\n parentName: \"a\"\n }, \"\\n \", mdx(\"source\", {\n parentName: \"picture\",\n \"srcSet\": [\"/static/4bf113dc4624bf177c3054ac7bef4935/e88ff/tech_debt.webp 600w\", \"/static/4bf113dc4624bf177c3054ac7bef4935/3697b/tech_debt.webp 971w\"],\n \"sizes\": \"(max-width: 971px) 100vw, 971px\",\n \"type\": \"image/webp\"\n }), \"\\n \", mdx(\"source\", {\n parentName: \"picture\",\n \"srcSet\": [\"/static/4bf113dc4624bf177c3054ac7bef4935/b4294/tech_debt.jpg 600w\", \"/static/4bf113dc4624bf177c3054ac7bef4935/6e9b1/tech_debt.jpg 971w\"],\n \"sizes\": \"(max-width: 971px) 100vw, 971px\",\n \"type\": \"image/jpeg\"\n }), \"\\n \", mdx(\"img\", {\n parentName: \"picture\",\n \"className\": \"gatsby-resp-image-image\",\n \"src\": \"/static/4bf113dc4624bf177c3054ac7bef4935/6e9b1/tech_debt.jpg\",\n \"alt\": \"Graph show Complexity vs. Risk\",\n \"title\": \"Graph show Complexity vs. Risk\",\n \"loading\": \"lazy\",\n \"decoding\": \"async\",\n \"style\": {\n \"width\": \"100%\",\n \"height\": \"100%\",\n \"margin\": \"0\",\n \"verticalAlign\": \"middle\",\n \"position\": \"absolute\",\n \"top\": \"0\",\n \"left\": \"0\"\n }\n }), \"\\n \"), \"\\n \"), \"\\n \")), mdx(\"p\", null, \"The overall debt levels were then converted into currency units, depicting the level of investment required to add new functionality into the system, e.g. only $0.1 of every $1 of any investment will go into innovation due to architectural technical debt. This is intended to help organizations build a business case for handling and removing architectural technical debt from their applications.\"), mdx(\"p\", null, \"We have shown a method to measure technical debt of an application based on the dependencies between its classes. We have successfully used this method to both identify local issues which cause technical debt as well as providing a global score, comparable between applications. By employing this method, organizations can successfully assess and manage the technical debt in their software which will lead to a better overall decision making process.\"), mdx(\"hr\", null), mdx(\"p\", null, mdx(\"em\", {\n parentName: \"p\"\n }, mdx(\"strong\", {\n parentName: \"em\"\n }, \"Bio:\"), \" Ori Saporta co-founded vFunction and serves as its Systems Architect. Prior to founding vFunction, Ori was the lead Systems Architect of WatchDox until its acquisition by Blackberry, where he continued to serve in the role of Distinguished Systems Architect. Prior to that, Ori was a Systems Architect at Israeli\\u2019s Intelligence Core Technology Unit (8200). Ori has a BSc in Computer Engineering from Tel-Aviv University and an MSc in Computer Science from the same institute for which his thesis subject was \\u201CTesting and Optimizing Data-Structure Implementations Under the RC11 Memory Model.\\u201D\")), mdx(\"div\", {\n \"className\": \"footnotes\"\n }, mdx(\"hr\", {\n parentName: \"div\"\n }), mdx(\"ol\", {\n parentName: \"div\"\n }, mdx(\"li\", {\n parentName: \"ol\",\n \"id\": \"fn-1\"\n }, \"Nord, Robert L., et al. \\u201CIn search of a metric for managing architectural technical debt.\\u201D \", mdx(\"em\", {\n parentName: \"li\"\n }, \"2012 Joint Working IEEE/IFIP Conference on Software Architecture and European Conference on Software Architecture\"), \". IEEE, 2012.\", mdx(\"a\", {\n parentName: \"li\",\n \"href\": \"#fnref-1\",\n \"className\": \"footnote-backref\"\n }, \"\\u21A9\")), mdx(\"li\", {\n parentName: \"ol\",\n \"id\": \"fn-2\"\n }, mdx(\"a\", {\n parentName: \"li\",\n \"href\": \"https://en.wikipedia.org/wiki/God_object\",\n \"target\": \"_blank\",\n \"rel\": \"noopener noreferrer\"\n }, \"Wikipedia: God object\"), \".\", mdx(\"a\", {\n parentName: \"li\",\n \"href\": \"#fnref-2\",\n \"className\": \"footnote-backref\"\n }, \"\\u21A9\")))));\n}\n;\nMDXContent.isMDXComponent = true;","frontmatter":{"date":"Jul 7, 2022","title":"A Method to Measure and Manage Technical Debt","description":"we demonstrate that not only is technical debt key to making decisions regarding any specific application, it is also important when attempting to prioritize work between multiple applications.","tags":["Metrics"],"image":{"childImageSharp":{"gatsbyImageData":{"layout":"fullWidth","backgroundColor":"#281818","images":{"fallback":{"src":"/static/9cc6f2b24305564673d654db03b74123/bf97f/banner.jpg","srcSet":"/static/9cc6f2b24305564673d654db03b74123/ffae8/banner.jpg 750w,\n/static/9cc6f2b24305564673d654db03b74123/271eb/banner.jpg 1080w,\n/static/9cc6f2b24305564673d654db03b74123/bf97f/banner.jpg 1254w","sizes":"100vw"},"sources":[{"srcSet":"/static/9cc6f2b24305564673d654db03b74123/5f165/banner.webp 750w,\n/static/9cc6f2b24305564673d654db03b74123/29464/banner.webp 1080w,\n/static/9cc6f2b24305564673d654db03b74123/0883c/banner.webp 1254w","type":"image/webp","sizes":"100vw"}]},"width":1,"height":0.45055821371610844}}}}}},"pageContext":{"id":"b02029b7-a34d-5c9d-8560-48f70b6e2df1","slug":"measure-manage-technical-debt/","__params":{"slug":"measure-manage-technical-debt"}}},"staticQueryHashes":["1129262270","1953051027","2744294623","287575728","3649515864","3663114508","4063661203"]} \ No newline at end of file +{"componentChunkName":"component---src-pages-blog-mdx-slug-js","path":"/blog/measure-manage-technical-debt/","result":{"data":{"mdx":{"id":"b02029b7-a34d-5c9d-8560-48f70b6e2df1","slug":"measure-manage-technical-debt/","body":"var _excluded = [\"components\"];\nfunction _extends() { _extends = Object.assign ? Object.assign.bind() : function (target) { for (var i = 1; i < arguments.length; i++) { var source = arguments[i]; for (var key in source) { if (Object.prototype.hasOwnProperty.call(source, key)) { target[key] = source[key]; } } } return target; }; return _extends.apply(this, arguments); }\nfunction _objectWithoutProperties(source, excluded) { if (source == null) return {}; var target = _objectWithoutPropertiesLoose(source, excluded); var key, i; if (Object.getOwnPropertySymbols) { var sourceSymbolKeys = Object.getOwnPropertySymbols(source); for (i = 0; i < sourceSymbolKeys.length; i++) { key = sourceSymbolKeys[i]; if (excluded.indexOf(key) >= 0) continue; if (!Object.prototype.propertyIsEnumerable.call(source, key)) continue; target[key] = source[key]; } } return target; }\nfunction _objectWithoutPropertiesLoose(source, excluded) { if (source == null) return {}; var target = {}; var sourceKeys = Object.keys(source); var key, i; for (i = 0; i < sourceKeys.length; i++) { key = sourceKeys[i]; if (excluded.indexOf(key) >= 0) continue; target[key] = source[key]; } return target; }\n/* @jsxRuntime classic */\n/* @jsx mdx */\n\nvar _frontmatter = {\n \"author\": \"ospaporta\",\n \"date\": \"2022-07-07T07:00:00.000Z\",\n \"description\": \"we demonstrate that not only is technical debt key to making decisions regarding any specific application, it is also important when attempting to prioritize work between multiple applications.\",\n \"featured\": false,\n \"image\": \"banner.jpg\",\n \"tags\": [\"Metrics\"],\n \"title\": \"A Method to Measure and Manage Technical Debt\"\n};\nvar layoutProps = {\n _frontmatter: _frontmatter\n};\nvar MDXLayout = \"wrapper\";\nreturn function MDXContent(_ref) {\n var components = _ref.components,\n props = _objectWithoutProperties(_ref, _excluded);\n return mdx(MDXLayout, _extends({}, layoutProps, props, {\n components: components,\n mdxType: \"MDXLayout\"\n }), mdx(\"p\", null, \"As a software developer, technical debt is all those little things that you feel are hampering the efficiency of your coding. These are the issues that you (or your manager) choose to handle next time, because of the urgency of the current release. But sometimes, by the time you get to them, they have become so big you do not know where to start solving them. The difficult part is that decisions we make regarding technical debt have to balance between short term and long term implications of accumulating such debt, emphasizing the need to properly assess and address it when planning development cycles.\"), mdx(\"p\", null, \"In their seminal article from 2012\", mdx(\"sup\", {\n parentName: \"p\",\n \"id\": \"fnref-1\"\n }, mdx(\"a\", {\n parentName: \"sup\",\n \"href\": \"#fn-1\",\n \"className\": \"footnote-ref\"\n }, \"1\")), \", Nord et al suggest a metric to measure technical debt, based on dependencies between architectural elements. They use this method to show how an organization should plan development cycles while taking into account the effect the technical debt will have on the overall resources required for each subsequent version.\"), mdx(\"p\", null, \"In this post, we demonstrate that not only is technical debt key to making decisions regarding any specific application, it is also important when attempting to prioritize work between multiple applications. Specifically, modernization work. Moreover, we show a method that can be used to not only compare the performance of different design paths for a single application, but also compare the technical debt levels of multiple applications at an arbitrary point in their development life cycle.\"), mdx(\"p\", null, \"The main idea of the aforementioned article is to provide a way to measure technical debt. It is done using a formula that mainly relies on the dependencies between architectural elements in the given application. It is worth noting that the article does not define what constitutes an architectural element or how to identify these elements when approaching an application.\"), mdx(\"p\", null, \"We took a similar approach and devised a method to measure technical debt of an application based on the dependency graph between its classes. The dependency graph is a directional graph \", mdx(\"em\", {\n parentName: \"p\"\n }, \"G\"), \" =(\", mdx(\"em\", {\n parentName: \"p\"\n }, \"V\"), \", \", mdx(\"em\", {\n parentName: \"p\"\n }, \"E\"), \") in which the \", mdx(\"em\", {\n parentName: \"p\"\n }, \"V\"), \" = {\", mdx(\"em\", {\n parentName: \"p\"\n }, \"c\"), mdx(\"sub\", null, \"1\"), \", \", mdx(\"em\", {\n parentName: \"p\"\n }, \"c\"), mdx(\"sub\", null, \"2\"), \", \\u2026} is the set of all classes in the application and an edge \", mdx(\"em\", {\n parentName: \"p\"\n }, \"e\"), \" = \\u27E8\", mdx(\"em\", {\n parentName: \"p\"\n }, \"c\"), mdx(\"sub\", null, \"1\"), \", \", mdx(\"em\", {\n parentName: \"p\"\n }, \"c\"), mdx(\"sub\", null, \"2\"), \"\\u27E9 \\u2208 \", mdx(\"em\", {\n parentName: \"p\"\n }, \"E\"), \" exists between two vertices if class \", mdx(\"em\", {\n parentName: \"p\"\n }, \"c\"), mdx(\"sub\", null, \"1\"), \" depends on class \", mdx(\"em\", {\n parentName: \"p\"\n }, \"c\"), mdx(\"sub\", null, \"2\"), \" in the original code. We perform multi-faceted analysis on the graph to eventually come up with a score that describes the technical debt of the application. Here are some of the metrics we extract from the raw graph:\"), mdx(\"ol\", null, mdx(\"li\", {\n parentName: \"ol\"\n }, \"Average/median outdegree of the vertices on the graph\"), mdx(\"li\", {\n parentName: \"ol\"\n }, \"Top N outdegree of any node in the graph.\"), mdx(\"li\", {\n parentName: \"ol\"\n }, \"Longest paths between classes\")), mdx(\"p\", null, \"Using standard clustering algorithms on the graph, we identify communities of classes within the graph and measure additional metrics on them, such as:\"), mdx(\"ol\", null, mdx(\"li\", {\n parentName: \"ol\"\n }, \"Average outdegree of the identified communities\"), mdx(\"li\", {\n parentName: \"ol\"\n }, \"Longest paths between communities\")), mdx(\"p\", null, \"Our hypothesis is that using these generic metrics on the dependency graphs, we can identify architectural issues which represent real technical debt in the original code base. Moreover, by analyzing dependencies on these two levels, class and community, we give a broad interpretation of what an architectural element is in practice, without attempting to formally define it.\"), mdx(\"p\", null, \"To test this method, we created a data set of over fifty applications from a variety of domains (online retail, financial, automotive, etc\\u2026) and extracted the aforementioned metrics from them. We used this data set in two ways. First, we correlated specific instances of high ranking occurrences of outdegrees and long paths with local issues in the code. For example, identifying god classes by their high outdegree\", mdx(\"sup\", {\n parentName: \"p\",\n \"id\": \"fnref-2\"\n }, mdx(\"a\", {\n parentName: \"sup\",\n \"href\": \"#fn-2\",\n \"className\": \"footnote-ref\"\n }, \"2\")), \". This proved efficient and increased our confidence level that this approach is valid in identifying local technical debt issues. The second approach was to try and provide a high level score that can be used not only to identify technical debt in a single application but to also be able to compare technical debt between applications, and to use it to help prioritize which should be addressed and how. To do that we introduced three indexes:\"), mdx(\"ol\", null, mdx(\"li\", {\n parentName: \"ol\"\n }, \"Complexity \\u2014 represents the effort required to add new features into the software.\"), mdx(\"li\", {\n parentName: \"ol\"\n }, \"Risk \\u2014 represents the potential risk that adding new features has on the stability of existing ones.\"), mdx(\"li\", {\n parentName: \"ol\"\n }, \"Overall Debt \\u2014 represents the overall amount of extra work required when attempting to add new features.\")), mdx(\"p\", null, \"We manually analyzed the applications in our data set, also employing the expert knowledge of the architects in charge of actively developing them, and scored each application\\u2019s complexity, risk, and overall debt on a scale of 1-5. We used these benchmarks to train a machine learning model which correlates the values of the extracted metrics with the indexes and normalizes them to a score of 0-100. At this point, we can use this trained model to issue a score per index for any new application we encounter which allows us to analyze entire portfolios of applications, and compare them both to one another and to our pre-calculated benchmark. 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This is intended to help organizations build a business case for handling and removing architectural technical debt from their applications.\"), mdx(\"p\", null, \"We have shown a method to measure technical debt of an application based on the dependencies between its classes. We have successfully used this method to both identify local issues which cause technical debt as well as providing a global score, comparable between applications. By employing this method, organizations can successfully assess and manage the technical debt in their software which will lead to a better overall decision making process.\"), mdx(\"hr\", null), mdx(\"p\", null, mdx(\"em\", {\n parentName: \"p\"\n }, mdx(\"strong\", {\n parentName: \"em\"\n }, \"Bio:\"), \" Ori Saporta co-founded vFunction and serves as its Systems Architect. Prior to founding vFunction, Ori was the lead Systems Architect of WatchDox until its acquisition by Blackberry, where he continued to serve in the role of Distinguished Systems Architect. Prior to that, Ori was a Systems Architect at Israeli\\u2019s Intelligence Core Technology Unit (8200). Ori has a BSc in Computer Engineering from Tel-Aviv University and an MSc in Computer Science from the same institute for which his thesis subject was \\u201CTesting and Optimizing Data-Structure Implementations Under the RC11 Memory Model.\\u201D\")), mdx(\"div\", {\n \"className\": \"footnotes\"\n }, mdx(\"hr\", {\n parentName: \"div\"\n }), mdx(\"ol\", {\n parentName: \"div\"\n }, mdx(\"li\", {\n parentName: \"ol\",\n \"id\": \"fn-1\"\n }, \"Nord, Robert L., et al. \\u201CIn search of a metric for managing architectural technical debt.\\u201D \", mdx(\"em\", {\n parentName: \"li\"\n }, \"2012 Joint Working IEEE/IFIP Conference on Software Architecture and European Conference on Software Architecture\"), \". IEEE, 2012.\", mdx(\"a\", {\n parentName: \"li\",\n \"href\": \"#fnref-1\",\n \"className\": \"footnote-backref\"\n }, \"\\u21A9\")), mdx(\"li\", {\n parentName: \"ol\",\n \"id\": \"fn-2\"\n }, mdx(\"a\", {\n parentName: \"li\",\n \"href\": \"https://en.wikipedia.org/wiki/God_object\",\n \"target\": \"_blank\",\n \"rel\": \"noopener noreferrer\"\n }, \"Wikipedia: God object\"), \".\", mdx(\"a\", {\n parentName: \"li\",\n \"href\": \"#fnref-2\",\n \"className\": \"footnote-backref\"\n }, \"\\u21A9\")))));\n}\n;\nMDXContent.isMDXComponent = true;","frontmatter":{"date":"Jul 7, 2022","title":"A Method to Measure and Manage Technical Debt","description":"we demonstrate that not only is technical debt key to making decisions regarding any specific application, it is also important when attempting to prioritize work between multiple applications.","tags":["Metrics"],"image":{"childImageSharp":{"gatsbyImageData":{"layout":"fullWidth","backgroundColor":"#281818","images":{"fallback":{"src":"/static/9cc6f2b24305564673d654db03b74123/bf97f/banner.jpg","srcSet":"/static/9cc6f2b24305564673d654db03b74123/ffae8/banner.jpg 750w,\n/static/9cc6f2b24305564673d654db03b74123/271eb/banner.jpg 1080w,\n/static/9cc6f2b24305564673d654db03b74123/bf97f/banner.jpg 1254w","sizes":"100vw"},"sources":[{"srcSet":"/static/9cc6f2b24305564673d654db03b74123/5f165/banner.webp 750w,\n/static/9cc6f2b24305564673d654db03b74123/29464/banner.webp 1080w,\n/static/9cc6f2b24305564673d654db03b74123/0883c/banner.webp 1254w","type":"image/webp","sizes":"100vw"}]},"width":1,"height":0.45055821371610844}}}}}},"pageContext":{"id":"b02029b7-a34d-5c9d-8560-48f70b6e2df1","slug":"measure-manage-technical-debt/","__params":{"slug":"measure-manage-technical-debt"}}},"staticQueryHashes":["1129262270","1953051027","2744294623","287575728","3649515864","3663114508","4063661203"]} \ No newline at end of file diff --git a/page-data/blog/metrics-driven-approach-to-transformation/page-data.json b/page-data/blog/metrics-driven-approach-to-transformation/page-data.json index cc99c89b..9babb0cc 100644 --- a/page-data/blog/metrics-driven-approach-to-transformation/page-data.json +++ b/page-data/blog/metrics-driven-approach-to-transformation/page-data.json @@ -1 +1 @@ -{"componentChunkName":"component---src-pages-blog-mdx-slug-js","path":"/blog/metrics-driven-approach-to-transformation/","result":{"data":{"mdx":{"id":"8fc56bbc-6d0e-5590-8abd-cce011fe89be","slug":"metrics-driven-approach-to-transformation/","body":"var _excluded = [\"components\"];\nfunction _extends() { _extends = Object.assign ? 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When we started providing professional services around enterprise Kubernetes, it became clear we needed a program-level framework for adopting containers that spelled out the activities of multiple project teams. Some participants would be focused on container platform management and operations, some on continuous delivery, some on the application lifecycle, and others on cross-cutting process transformation.\"), mdx(\"p\", null, \"We\\u2019ve had success using this framework to help customers rethink container adoption as less a matter of new technology implementation and more as an \\u201Corganizational journey,\\u201D where people and process concerns are at least as important as the successful deployment of OpenShift clusters.\"), mdx(\"p\", null, \"Over time, we\\u2019ve realized the program framework is missing a guiding force that gets executive stakeholders engaged and can keep all participants focused on a consistent, meaningful set of objectives. 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And we have a set of practices that can be applied against this technology backdrop, using containers and container platform as accelerators of those practices when possible.\"), mdx(\"p\", null, \"The focus for the authors is on global performance, not local optimization, and on \\u201Coutcomes not output,\\u201D so the organization rewards activities that matter, rather than sheer volume of activity. This last point is crucial. In an \", mdx(\"a\", {\n parentName: \"p\",\n \"href\": \"https://blog.openshift.com/assessing-app-portfolios-for-onboarding-to-openshift/\",\n \"target\": \"_blank\",\n \"rel\": \"noopener noreferrer\"\n }, \"earlier post\"), \", I wrote about app onboarding to OpenShift. Taken to the extreme, a myopic focus on the percentage of the portfolio or number of apps migrated to X (containers, Kubernetes, OpenShift, AWS, \\u201CThe Cloud\\u201D) is a focus on \", mdx(\"em\", {\n parentName: \"p\"\n }, \"outputs not outcomes\"), \". 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Since then, the project has undergone a series of transformative changes and remarkable achievements, guided by a newly \", mdx(\"a\", {\n parentName: \"p\",\n \"href\": \"https://github.com/konveyor/community/blob/main/Charter.md\",\n \"target\": \"_blank\",\n \"rel\": \"noopener noreferrer\"\n }, \"updated charter\"), \" that has refocused Konveyor\\u2019s mission towards refactoring and replatforming legacy applications. In this post, we invite you to join us on a journey down memory lane as we celebrate the numerous milestones, both big and small, that our dedicated contributors have accomplished over the past year.\"), mdx(\"p\", null, \"In the initial months following Konveyor\\u2019s acceptance into the CNCF sandbox, considerable effort was invested in establishing essential contributor documentation, forming a steering committee, and embracing best practices for repository management. We extend our heartfelt gratitude to \", mdx(\"a\", {\n parentName: \"p\",\n \"href\": \"http://berkus.org/\",\n \"target\": \"_blank\",\n \"rel\": \"noopener noreferrer\"\n }, \"Josh Berkus\"), \" and \", mdx(\"a\", {\n parentName: \"p\",\n \"href\": \"https://www.linkedin.com/in/lenka-bo%C4%8Dincov%C3%A1-0602a493/\",\n \"target\": \"_blank\",\n \"rel\": \"noopener noreferrer\"\n }, \"Lenka Bo\\u010Dincov\\xE1\"), \" from Red Hat OSPO for their invaluable guidance in onboarding Konveyor into the CNCF. \", mdx(\"a\", {\n parentName: \"p\",\n \"href\": \"https://github.com/cncf/tag-contributor-strategy\",\n \"target\": \"_blank\",\n \"rel\": \"noopener noreferrer\"\n }, \"CNCF TAG-Contribex\"), \" has developed \", mdx(\"a\", {\n parentName: \"p\",\n \"href\": \"https://contribute.cncf.io/maintainers/templates/\",\n \"target\": \"_blank\",\n \"rel\": \"noopener noreferrer\"\n }, \"project templates\"), \" that played a vital role in expediting our onboarding process. These templates encompassed everything from code of conduct to vulnerability management, demonstrating the thoughtful process of the TAG-Contribex team in helping project maintainers onboard easily. \"), mdx(\"p\", null, \"With the revised charter, Konveyor\\u2019s mission has now evolved to \\u201CAccelerate the adoption of Kubernetes by assisting organizations in modernizing their legacy applications with Kubernetes and cloud-native technologies in a secure and predictable manner at scale, delivering value at every stage of the adoption journey.\\u201D The project\\u2019s future vision is encapsulated in the \", mdx(\"a\", {\n parentName: \"p\",\n \"href\": \"https://github.com/konveyor/enhancements/tree/master/enhancements/unified_experience\",\n \"target\": \"_blank\",\n \"rel\": \"noopener noreferrer\"\n }, \"Unified Experience\"), \", which serves as our guiding light for all development efforts. The evolution of Konveyor\\u2019s roadmap is clearly evident, commencing with the initial emphasis on surfacing information in its 0.1 release. Subsequent release 0.2, extended this focus to enable the planning of work in the form of migration waves, culminating in a significant milestone in 0.3 - a comprehensive rewrite of the analysis engine. This rewrite is built upon the Language Server Protocol, laying the foundation for multi-language analysis capabilities. Currently, this feature supports Java and Go, with active development underway to extend this support to .NET/C#.\"), mdx(\"p\", null, \"We are excited to share that \", mdx(\"a\", {\n parentName: \"p\",\n \"href\": \"https://claranet.com\",\n \"target\": \"_blank\",\n \"rel\": \"noopener noreferrer\"\n }, \"Claranet\"), \" is the latest contributor and community supporter of Konveyor. 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We wanted to dig deeper into the specifics. To do so, Konveyor community contributor Red Hat sponsored a survey of 600 IT decision makers (ITDM), backend developers, and software architects in the US, UK, and English-speaking Asia-Pacific (APAC).","content":"---\ntitle: State of Application Modernization Report 2022\ndescription: >-\n Both anecdotes and past surveys tell us that organizations are modernizing their applications. We wanted to dig deeper into the specifics. To do so, Konveyor community contributor Red Hat sponsored a survey of 600 IT decision makers (ITDM), backend developers, and software architects in the US, UK, and English-speaking Asia-Pacific (APAC).\nbanner: report-22-banner.jpg\nshare_image: /images/report-22.jpg\n---\n\nimport MainCol from '../../components/main-col'\nimport SidebarTOC from '../../components/sidebar-toc'\n\n\n\n```toc\n#TOC will render here\n```\n\n\n\n\n\nby Gordon Haff\n\nBoth anecdotes and past surveys tell us that organizations are modernizing their applications. We wanted to dig deeper into the specifics. To do so, Konveyor community contributor Red Hat sponsored a survey of 600 IT decision makers (ITDM), backend developers, and software architects in the US, UK, and English-speaking Asia-Pacific (APAC). We surveyed these respondents, drawn from third-party databases, in October and November of 2021. Their companies had to have an internal app dev team and had to be using or planning to use hybrid cloud or multicloud as well as containers (the overwhelming majority were already using both). Here are some of the things they told us.\n\n## Modernization is happening quickly\n\n![Companies plan for more than half of their custom applications to be modernized within the next year.](modernization-plan.svg)\n\nWe sought out respondents who were modernizing or planning to modernize their custom apps in some manner, so it’s no surprise that everyone we surveyed is modernizing. What’s perhaps less expected is how quickly they’re planning to modernize. Companies are planning to modernize over half of their custom applications during the next year and over a quarter during the next six months. Only 20% expected the modernization to take more than two years.\n\nDoes that seem a bit… optimistic? It does. Indeed, as was something of a theme throughout this survey, developers were less confident than their ITDM and architect counterparts that modernization would be either quick or straightforward.\n\nThe barriers cited by respondents provide additional evidence that modernization projects won’t always be smooth sailing. All regions except the UK said that resistance to change was the top barrier—and in the UK it was still near the top. The fact that this is a cultural challenge far more than a technical one suggests that overcoming such a barrier may be difficult and require senior management buy-in. Other top barriers were related concerns like time constraints, cost and budget constraints, and lack of skilled resources. Skills shortages in particular are a common theme almost across the board when we conduct surveys about important IT initiatives.\n\nHowever, even if you think that a lot of modernization projects are likely to slip out, the data certainly points to an intent to rapidly modernize.\n\n## There’s no single app modernization strategy\n\n![Companies intend to replatform, refactor, or repurchase just over half of their custom legacy applications.](replatform-plan.svg)\n\nIn considering app modernization strategies, we presented survey respondents with six choices, the widely used six Rs. These are:\n\n- **Retire:** Sunset or decommission applications that are no longer needed\n- **Retain:** Leave critical applications as-is until refactoring is required\n- **Rehost:** Copy applications to a cloud (whether hosted or on-prem) with minimal changes, i.e. “lift and shift”\n- **Replatform:** Use a cloud migration to upgrade operating systems, databases, and other components as needed in order to cloud-enable applications without changing core application code or architecture\n- **Refactor:** Re-architect as cloud-native, for example, by containerizing workloads or moving them to a serverless architecture\n- **Repurchase:** Move from perpetual licenses to a Software-as-a-Service (SaaS) model\n\nThat’s quite the range of options and they’re all being used to significant degrees. Retire and retain were each about half as popular than the four other options — which each captured about 20% of the applications being modernized. The overall story is definitely about matching the application modernization strategy to a given workload and company need rather than there being a single dominant approach across companies.\n\nWe again see developers being more cautious or pessimistic about more aggressive modernization approaches; they were more likely to intend to rehost relative to ITDMs and architects. We sometimes hear about “resume-driven development,” whereby developers supposedly want to gain experience in new technologies, even if doing so increases complexity. However, the developers in our survey were more likely to favor lower risk and lower effort approaches.\n\nWe also found that refactoring, which is the most involved modernization approach, is almost always a two-step approach. 90% of those who plan to refactor any legacy apps intend to replatform them first.\n\n## The US is further along than others\n\n
                          \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
                          USUKAPAC
                          Unique Definitions of App ModernizationUsing microservices architecture in the cloudImproving CI/CDImproving CI/CD
                          Unique Reasons for App ModernizationDecrease costsDecrease costsImprove security improve customer experience
                          Unique Barriers\n
                            \n
                          • Difficulty determining the right approach
                            • \n
                          • Do no see the value of modernizing
                            • \n
                          \n                           		Have not faces any barriersHave not faced any barriers
                          Unique ChallengesDifficulty determining the right approachNo differentiating challengesNo differentiating challenges
                          Unique Success MeasuresDecreased costincreased customer satisfactionImproved security increased customer satisfaction
                          Legacy App StrategyMore likely to retire or retain applicationsMore likely to rehost or repurchase applicationsMost likely to rehost or repurchase applications
                          Unique App Modernization PrioritiesNo differentiating PrioritiesData/analytics/BI applications\n
                            \n
                          • Customer-facing applications
                            • \n
                          • Data/analytics/BI applications
                            • \n
                          \n
                          \n
                          \n\nWe don’t generally find striking differences between regions but we do sometimes see more subtle ones that form something of a pattern, as was the case here.\n\nIn this case, we see the US uniquely defining app modernization as “Using microservices architecture in the cloud” while the other two regions defined it as “Improving CI/CD.” This suggests that the US is further along in app modernization. Having a well-developed CI/CD pipeline is foundational to microservices and other cloud-native technology approaches.\n\nWe see something similar crop up with respect to barriers and challenges. The UK and APAC haven’t faced any barriers. It’s reasonable to assume that’s because they haven’t gotten far enough into the process yet. By contrast, the US is focused on the “Difficulty determining the right approach,” suggesting that they’re actively figuring out the best way to implement a modernization strategy across their application portfolio.\n\n## Increasing scalability and reliability trump cost reductions\n\n![Companies plan to measure success of application modernization base on increased reliability and increased scalability.](measurement-plan.svg)\n\nHow are companies going to measure the success of their application modernizations? Decreased costs are one factor. Costs always matter to at least some degree; ask anyone who has ever owned a budget. But increased reliability (especially in the US) and scalability were at the top of the list overall, with security high up as well.\n\nThis was a question that had significant regional differences. Improving security was a significantly higher-ranked measure in APAC than in other regions and even edged out increased scalability there. APAC was also much more likely to measure increased customer satisfaction—especially relative to the US.\n\n## AI/ML, data caching, and high performance computing on the upswing\n\n![More companies expect to have AI/ML software, data caching tools, and high performance computing workloads in place in the next 2 years.](ai-ml.svg)\n\nWhile traditional workloads such as web servers, business process applications, and databases are the most common today, they’re not where workload growth is expected to be over the next two years. That would be AI/ML software, data caching (think Redis), and high performance computing, which are expected to grow at least 20% during that period. Analytics falls in between the two groups both in terms of level of usage today and its expected rate of growth.\n\nThus, many new applications and application architectures are likely to be in emerging technology areas which include these high growth workloads. While most of the workloads were fairly consistent across regions, AI/ML in the US (68%) was markedly higher than in the UK (57%) which was higher than in APAC (43%).\n\n## Is there a public cloud backlash?\n\n![Companies expect a shift from public cloud toward private cloud deployment 2 years from now, especially in the UK and APAC.](private-cloud-shift.svg)\n\nThe overwhelming majority of the companies we surveyed run at least some of their production applications on a public cloud although a significant number also run on a private cloud—whether on-premise, off-premise, or both.\n\nThe most striking thing about these numbers though is where they’re headed. The 98% of companies that have at least some production workloads on a public cloud today is expected to drop ten points over the next two years to 88%. This drop is almost entirely attributable to the UK and APAC with the US dropping only one point. In APAC specifically, a full 26% of companies plan to stop using public clouds for production workloads; most of those workloads would appear to be going to off-premise private clouds which have a commensurately large expected increase.\n\nWhat’s going on? Are public clouds falling out of favor?\n\nThere’s some anecdotal evidence that data egress and a general lack of cost predictability have driven some companies to repatriate certain applications to private clouds. Furthermore, edge computing architectures distribute workloads so as to bring compute resources closer to data and user services. (Although they still often have a cloud component, whether on a public cloud or on-premise.)\n\nHowever, in the US, the percentage of companies with one or more production workloads on a public cloud is expected to stay essentially flat. This suggests that the significant expected shift in the UK and APAC numbers probably isn’t explained by cost and edge computing alone.\n\nBased on other surveys we’ve conducted, those other reasons may relate to data privacy, data security, and data sovereignty concerns. It’s not a stretch to imagine that these concerns might be heightened in the UK and APAC, especially in light of the fact that the three large global public cloud providers are all headquartered in the US.\n\nThe above notwithstanding, however, backlash is probably too strong a term. Rather, with 77% already having a hybrid cloud infrastructure, the results suggest that companies are just increasingly sophisticated in placing workloads on the best kind of infrastructure for the purpose rather than taking more of a one-size-fits-all approach.\n\n## Slide deck with all findings\n\n\n\n[State of application modernization 2022](https://www.slideshare.net/KonveyorIO/state-of-application-modernization-2022) from [Konveyor Community](https://www.slideshare.net/KonveyorIO)\n\n---\n\n_Gordon Haff is Technology Advocate at Red Hat where he works on emerging technology strategy; writes about tech, trends, and their business impact; and is a frequent speaker at customer and industry events. Among the topics he works on are edge, blockchain, AI, quantum, cloud-native platforms, and next-generation application architectures. His books include From Pots and Vats to Programs and Apps and How Open Source Ate Software. His current podcast is Innovate @ Open. Prior to Red Hat, as an industry analyst, Gordon wrote hundreds of research notes, was frequently quoted in major publications on a wide range of IT topics, and advised clients on product and marketing strategies._\n\n                          \n"},"12cda7c0-1878-5c73-9ed1-b19f21c3c3b5":{"id":"12cda7c0-1878-5c73-9ed1-b19f21c3c3b5","title":"Application Modernization Report Shows Need For Kubernetes-specific Migration Tooling","slug":"/application-modernization-report/","description":"In MTC 1.4.0, a new feature called Direct Migration is available that will yield significant time savings for most customers migrating persistent volumes and/or internal images.","tags":["Kubernetes"],"content":"---\nauthor: ghaff\ndate: 2022-03-09T07:00:00Z\ndescription: >-\n In MTC 1.4.0, a new feature called Direct Migration is available that will yield significant time savings for most customers migrating persistent volumes and/or internal images.\nfeatured: true\nimage: report-22-banner.jpg\ntags:\n - Kubernetes\ntitle: Application Modernization Report Shows Need For Kubernetes-specific Migration Tooling\n---\n\nKonveyor is a community of people passionate about helping others modernize and migrate their applications to the hybrid cloud by building tools, identifying patterns, and providing advice on how to break down monoliths, adopt containers, and embrace Kubernetes. To do so the Konveyor community is currently working on five projects to help users rehost, replatform, and refactor their applications to Kubernetes.\n\nWhile conversations with users and data from various sources gave us some visibility into how migrations were taking place, we wanted to inform our priorities with recent detailed data. To do so, Red Hat, a Konveyor community contributor, sponsored a survey of 600 IT decision makers, backend developers, and software architects in the US, UK, and English-speaking Asia-Pacific (APAC) to better understand the application modernization landscape.\n\nHere are some of the findings that relate to Konveyor and application modernization:\n\n## Application modernization is happening now\n\nIt’s clear that there is urgency to roll out migration tooling. Among those we surveyed, those who were migrating or planning to, we found that they plan to modernize over half of their custom applications during the next year and over a quarter during the next six months. Only 20% expected the modernization to take more than two years. It’s clear this is happening right now.\n\nThat said, it’s not all smooth sailing and this doesn’t happen overnight. While some regions haven’t progressed far enough in their application modernization journey to experience serious barriers, others (notably the US) report that choosing a straightforward approach can be challenging. Organizations have many options to choose from and each option presents varying levels of complexity.\n\n![Companies plan for more than half of their custom applications to be modernized within the next year.](modernization-plan.svg)\n\n## Motivators for modernizing existing applications to Kubernetes\n\nThe survey tells us modernization is mostly being driven by the need for reliability, scalability and security. Decreasing costs were also on the list but, as we frequently see in other surveys about technology adoption or change, it’s not the driving factor.\n\n![Most companies decide to modernize their applications to increase scalability or reliability. Companies in APAC also seek to improve security and customer experience, while those in the US and UK want to decrease costs.](increase-scalability.svg)\n\nKonveyor's tool suite can be used to help realize organization’s migration plans.\n\n![How migration strategies companies intend to use based on this survey map to the Konveyor Tool Suite.](map-to-konveyor.svg)\n\nThe Konveyor tool suite maps closely to the migration strategies companies intend to use based on this survey: rehosting, replatforming, and refactoring.\n\n![Companies intend to replatform, refactor, or repurchase just over half of their custom legacy applications.](replatform-plan.svg)\n\n## Rehost applications to cloud with Forklift and Crane\n\nRehosting (20% of total) involves copying applications to a cloud (whether hosted or on-prem) with minimal changes, i.e. “lift and shift.” This will be familiar to anyone with experience in virtualization early on when bare metal servers were often moved to a virtual machine (VM) for greater efficiency but with little or no changes to the software and with relatively modest operational changes.\n\nWhile rehosting doesn’t provide the same depth of benefits as replatforming or refactoring, it’s the first step in the right direction. Rehosting was the single most common approach\n**Forklift** and **Crane** are the relevant Konveyor projects here. Forklift is focused on migrating VMs to Kubernetes and provides the ability to migrate multiple VMs to KubeVirt with minimal downtime.\n\nCrane is a rehosting tool that meets a different use case. Crane helps organizations to migrate applications between Kubernetes clusters. There are many times when developers and operations teams want to migrate between older and newer versions of Kubernetes, evacuate a cluster, or migrate to different underlying infrastructure.\n\n## Replatforming applications with Move2Kube\n\nReplatforming (18% of total) is using a cloud migration to upgrade operating systems, databases, and other components as needed in order to cloud-enable applications without changing core application code or architecture. Think of it as “lift, tinker, and shift.”\n\nThis is effectively an intermediate step between just rehosting and refactoring. In fact, it’s often a stepping stone; the survey found that 90% of those planning to refactor their apps plan to replatform them first.\n\n**Move2Kube** is a Konveyor project that allows customers to replatform their applications to Kubernetes orchestrated platforms. One area where replatforming is taking place is in the consolidation of container orchestration platforms to Kubernetes.\n\nDue to this consolidation, the Move2Kube project was started to focus on accelerating the process of replatforming to Kubernetes from platforms such as Swarm and Cloud Foundry. This project translates existing artifacts to Kubernetes artifacts to speed up the process of being able to run applications on Kubernetes.\n\n## Refactoring applications with Tackle\n\nRefactoring (17%) is often viewed as the most challenging application modernization strategy but it's the one with the most long-term impact. Refactoring involves re-architecting as cloud-native, for example, by containerizing workloads, transforming a monolith to microservices, or moving functions to a serverless architecture.\n\nWhile **Tackle** is not a full refactoring tool, it provides a series of interrelated tools that allow users to assess, analyze, and ultimately move their applications onto a Kubernetes orchestrated platform.\n\n---\n\nAs you can see, organizations are taking a thoughtful approach to app migration and there’s no single right path. This data supports the Konveyor community’s approach of providing a toolbox, rather than just a singular tool, that can support transitioning applications however it is happening.\n"},"35c98cc0-f22c-58d0-b62d-48bcada7c94f":{"id":"35c98cc0-f22c-58d0-b62d-48bcada7c94f","title":"Community Update: Konveyor Refocuses Efforts on Replatforming and Refactoring Use Cases","slug":"/community-update-konveyor-refocuses-efforts/","description":"We recently revealed upcoming changes to the Konveyor Project. These adjustments are designed to solve the most important application modernizations problem better and to encourage participation with our community.","tags":["Crane","Forklift","Move2Kube","Pelorus","Tackle"],"content":"---\nauthor: konveyor\ndate: 2022-10-20T07:00:00Z\ndescription: >-\n We recently revealed upcoming changes to the Konveyor Project. These adjustments are designed to solve the most important application modernizations problem better and to encourage participation with our community.\nfeatured: true\nimage: banner.jpg\ntags:\n - Crane\n - Forklift\n - Move2Kube\n - Pelorus\n - Tackle\ntitle: 'Community Update: Konveyor Refocuses Efforts on Replatforming and Refactoring Use Cases'\n---\n\nIn the latest [community update](https://youtu.be/jyd3mpvVCC4), we revealed upcoming changes to the Konveyor Project. These adjustments are designed to solve the most important application modernizations problem better and to encourage participation with our community. Here’s what we announced:\n\n- We will solely focus on solving for the replatforming and refactoring use cases.\n- It’s easier to contribute and collaborate with Konveyor thanks to our new special interest group (SIG) model.\n- You can learn the Konveyor project, see upcoming features, and give us feedback at our workshop — part of the OpenShift Commons Gathering at KubeCon NA 2022. [Register for the Gathering](https://hopin.com/events/openshift-commons-gathering-2022-at-kubecon-na-detroit) to secure your spot.\n- Tackle 2.1 is available, future Tackle releases will be branded Konveyor.\n- Konveyor roadmap includes migration wave management, multi language support, and integrations with modernization tools.\n\nYou can get the details of each announcement below.\n\n## We are refocusing efforts on replatforming and refactoring use cases\n\nA key insight the [State of Application Modernization Report](/modernization-report/) surfaced is that users are more interested in replatforming and refactoring then just rehosting workloads or “lifting and shifting”. Paired with feedback from users, this revealed a gap in the tooling for refactoring which Konveyor is now addressing\n\nOriginally, Konveyor took a “big tent” approach to rehosting, replatforming and refactoring. We brought the tooling to a community of engineers, developers, and users to figure out what problems they need to solve. Now, due to their feedback, Konveyor is refocusing on just replatforming and refactoring, meaning:\n\n- Pelorus, Tackle and Move2Kube will be integrated and moved into a single project, now called Konveyor.\n- Crane (rehosting from one Kubernetes cluster to another) will be moved into a separate GitHub organization.\n- Forklift (rehosting to VMs) will move into a KubeVirt project focused on running VM’s with Kubernetes.\n\nCrane and Forklift will continue to exist but will no longer be part of the core Konveyor toolset.\n\n![Project changes: chart showing what will happen to each of the subprojects after the refocus.](project-changes.svg)\n\n## Special interest group (SIG) model makes it easier to contribute and collaborate with the project\n\nOne of the major changes to the Konveyor project is the refocusing on the major areas of code, UI, analyzers, and add-ons, each of which is represented by a special interest group (SIG) modeled after the SIGs created by the Kubernetes community. These groups are responsible for the development, integration, maintenance, and collaboration of the project.\n\nThe SIG Core is responsible for all of the core features of the Konveyor platform. These features include but are not limited to modernization, report generation, integration of program management tools, and the design of implementation of the hub itself.\n\nSIG UI is responsible for the user interface and experience across the platform. This SIG is also responsible for creating a pattern where all of the add-ons can be dynamically integrated into the hub.\n\nThe SIG Analyzers are working on creating an extensible pattern and standardization of input and output for the community to collaborate on the analyzers. The analyzers will each target specific programming languages.\n\nFinally SIG Add-ons are responsible for the development and integration of add-ons that will enhance Konveyor’s capabilities.\n\nThe community meetings bring together contributors and collaborators to provide a forum to discuss topics and new ideas and generate innovation, and happen on every first and third Thursday at 9 AM ET ([meetings are recorded](https://youtu.be/tiEJEiT8XtI)). Topics include milestones and features of upcoming releases, contributor showcases with member feedback. Above all, these meetings are intended to foster the community around Konveyor.\n\nThere are also many asynchronous opportunities to communicate and collaborate around Konveyor.\n\n- There is a #konveyor channel on the Kubernetes Slack channel. You can use it to ask any question about the project.\n- Contributors can subscribe to the [_Konveyor-community email list_](https://groups.google.com/u/0/g/konveyor-community) for community meeting invites and discussions to influence the direction of the community.\n- To get general updates, you can subscribe to the [email list](/community/#sign-up).\n- Or for more information, look at the Konveyor community repo — it includes information around governance documents, contributor letter, Get Started Guide, meeting agendas and developer notes.\n\n## Attend the Konveyor workshop at KubeCon North America 2022\n\nWe will run a workshop in the OpenShift Commons Gathering on 25 October, 2022. At this free, hands-on workshop, workshop leaders will take you through an assesment and analysis of a sample application using the Konveyor platform, followed by discussion of the Konveyor Roadmap and Q&A. Whether you are starting or continuing your application modernization journey, this is a great opportunity to learn how to contribute, or just how to use the tools. If you have any questions or just want to connect with the community or workshop, please reach out to Savita Raghunathan at [sraghuna@redhat.com](mailto:sraghuna@redhat.com) or on [Slack](/slack/).\n\n### How to register:\n\n- [Visit registration site](https://hopin.com/events/openshift-commons-gathering-2022-at-kubecon-na-detroit) and follow the directions below\n- Click \"register\"\n- Select \"Konveyor workshop\"\n- Click \"continue\"\n- Provide your info and submit\n\n## Tackle 2.1 is available, future Tackle releases will be branded Konveyor\n\nTackle 2.1 is available, with the ability to upgrade your current Tackle 2.0. Tackle 2.1 will be the final Tackle release. Future releases will bear the name Konveyor, and will begin with version 3.\n\nThe release of Konveyor 3 is envisioned for Q1 2023 pending the restructuring of the architecture, and some specific components to make contribution easier. For some of the more visionary components of Konveyor 4, the goal is to have these features ready for release in 2H 2023.\n\nIn Tackle 2.1 there are several important features:\n\nIntegration with [**DiVA** (_Data intensive Validity Advisor_)](https://github.com/konveyor/tackle-diva), which is now seamlessly integrated with Tackle: everything is available in the domain user interface to enable the new analysis mode. A transcription report tab is now included in analysis reports with detail on the data layer of your applications.\n\nThe next important feature is the ability to bulk delete applications. Before 2.1 it was possible to import applications in bulk, but not delete them. It will also include automated creation of missing entities on CSV import.\n\nNew rules will be included in the next patch to 2.1.1, allowing new migration paths for open JDK 11 to 17 rules, and with Microsoft as a new major player in the Konveyor community, migration to EAP and Spring Boot applications on top of Azure App Service is supported.\n\nFinally, the Konveyor community did a ton of bug fixing and optimization making this release much more stable than Tackle 2.0.\n\n## Konveyor roadmap\n\n![Diagram showing Konveyor roadmap for the next year](roadmap.svg)\n\nLooking forward to next year, several important features are visualized for the first release of Konveyor 3. First of these is **Migration Waves Management**. No one does a “big bang migration” when dealing with thousands of applications, but rather distributes application portfolio modernization across multiple waves. This new feature offers an assisted method for managing these waves, integrated into the main Konveyor user interface.\n\nFull integration with [**Tackle Test Generator**](https://github.com/konveyor/tackle-test-generator-cli) and [**Tackle Container Advisor**](https://github.com/konveyor/tackle-container-advisor#readme) in the main user interface is envisioned for this release as well. With Tackle Test Generator, tests for an application can be stored in your Git repository with a single click.\n\nTackle Container Advisor will leverage its’ entity standardization capability using the natural language description of the technology stack of the application, making it easier to ingest data at scale, simplifying CSV imports and Excel importing, and eliminating the need to code the technology stack as a series of separate tasks\n\n_Integration with Jira_ will allow the user to track and manage the whole migration process. Tackle will allow delegation of implementation to external issue managers or task managers. By creating issues in Jira related to the applications within the portfolio, a project leader can then assign them to developers to perform changes in the application portfolio.\n\n_Custom Migration Targets_ will be improved by abstracting users away from the complexities of having to assign custom rules without having to deal with these custom rules directly. Information and status on this feature should be available soon.\n\n_Custom rule upload_ to repositories will be integrated going forward to allow these rules to be uploaded automatically, and to be retrieved to and from source code repositories.\n\n_Tag management_ will also be improved, with numerous tags assigned to applications it is difficult for the UI to scale this information or consume it. This feature will help make these tags easier to consume.\n\nLooking even further into the future, Konveyor 4 will bring a whole new set of advanced features including multi language support for analysis, manifest generation and enhanced assessment module.\n\nEvery time Konveyor has been presented to an organization, invariably there is a request for multi language support. In an early prototype the Konveyor community has demonstrated the ability to use language server technology from Microsoft, decoupling the analysis from data models supporting analysis results. It’s very possible that this feature will be ready to ship with Konveyor 4 in May.\n\n_Manifest generation_ is another important feature: once you’ve successfully adapted source code to run on containers, this will then install the manifest on Kubernetes.\n\nFinally, feedback on the current **Assessment Module** is that it’s too opinionated, so the goal is to make it more intelligent and flexible.\n\nAltogether, the Konveyor Project has undergone a major transformation improving and simplifying, and creating new and better opportunities for building a community around Application Modernization centered around replatforming and refactoring.\n"},"54d9c5f1-8225-54fa-930c-37662b36595a":{"id":"54d9c5f1-8225-54fa-930c-37662b36595a","title":"Migrating Faster with Direct Migration","slug":"/direct-migration/","description":"In MTC 1.4.0, a new feature called Direct Migration is available that will yield significant time savings for most customers migrating persistent volumes and/or internal images.","tags":["MTC"],"content":"---\nauthor: dmurray\ndate: 2021-02-24T07:00:00Z\ndescription: >-\n In MTC 1.4.0, a new feature called Direct Migration is available that will yield significant time savings for most customers migrating persistent volumes and/or internal images.\nfeatured: true\nimage: banner.jpg\ntags:\n - MTC\ntitle: Migrating Faster with Direct Migration\n---\n\nIn MTC 1.4.0, a new feature called Direct Migration is available that will yield significant time savings for most customers migrating persistent volumes and/or internal images. Direct Migration enables the migration of persistent volumes and internal images directly from the source cluster to the destination cluster without an intermediary replication repository. This introduces a significant performance enhancement while also providing better error and progress reporting information back to the end-user.\n\nPrior MTC releases only allowed a 2 step backup and restore process when handling images and persistent volumes, which didn't take advantage of potential performance savings in the case of a migration with both the source and destination clusters having network connectivity. The prior process leveraged a filesystem copy tool called Restic integrated with Velero. MTC would need to copy PV and Image data twice: once from the source cluster to the replication repository, and a second time from the replication repository to the destination cluster. This process yielded flexibility for various environments, yet failed to take advantage of the more common case in a migration of direct network connectivity between clusters.\n\nWith Direct Migration in MTC 1.4, we are able to take advantage of any environments that have network connectivity between the clusters involved in the migration by handling the migration of PV data and Image data in a new way. Assuming remote clusters have exposed routes to enable external access to the internal registry, MTC will push internal images directly into the internal registry on the destination cluster from the source cluster. Assuming the clusters can communicate over port 443 via OpenShift routes, MTC will directly migrate Persistent Volume data from a source cluster to a destination cluster using a set of Rsync + Stunnel pods which we will describe more below.\n\n## Prerequisites\n\nAs mentioned above for direct image migrations, it is important for remote source and destination clusters internal registries be exposed for external network traffic.\n\n- [expose OCP 4 cluster registry](https://docs.openshift.com/container-platform/4.6/registry/securing-exposing-registry.html)\n- [expose OCP 3 cluser registry](https://docs.openshift.com/container-platform/3.11/install_config/registry/securing_and_exposing_registry.html)\n\nFor direct volume migrations, the source and destination clusters must be able to communicate over port 443 via OpenShift routes. MTC will create a route in each namespace to be migrated on the destination cluster and will be migrating the data by establishing an Rsync connection to this route. This means that the OpenShift routes must be accessible by the source cluster.\n\n![Configuration of 3 clusters running MTC](mtc-cluster.png)\n\nThe above diagram shows a configuration of 3 clusters running MTC. The Host cluster does not need to be its own cluster and could be the source or the destination cluster.\n\n## Direct Image Migration Details\n\nIn direct image migration (DIM), the Migration Controller pod creates a DIM resource that contains a list of namespaces to migrate. The DIM controller then finds all of the imagestreams with internal image references in those namespaces and copies them directly into the destination registry. In order for this to succeed, DIM also ensures the namespace exists on the destination cluster prior to the copy.\n\n![Clusters using DIM for migration](dim.png)\n\nThe above diagram shows how DIM orchestrates the migration of an imagestream backed by the internal registry directly from the source cluster to the destination cluster.\n\n## Direct Volume Migration Details\n\nFor Direct Volume Migration, or DVM, the DVM controller takes in a list of PVCs to migrate and performs a few steps prior to copying the data over. For DVM to work, it is necessary for the source and destination clusters to be able to communicate over port 443 via OCP routes which are created by DVM.\n\nFirst, DVM sets up the needed configuration configmaps and secrets across all the namespaces to migrate and then creates transfer pods on the destination cluster in each namespace to be migrated. The transfer pods on the destination include both rsyncd and stunnel containers. Stunnel is used to open up a communication tunnel between the source and destination. The rsyncd container has volume mounts to all PVCs in the namespace which are to be migrated. An rsync client pod is created on the source (1 per PVC) to then rsync the data via the stunnel route.\n\n![MTC orchestrating a direct migration](migrating.png)\n\nThe above diagram shows how MTC orchestrates a direct volume migration by standing up a set of rsync and stunnel pods to directly migrate the PV data from the source to the destination cluster.\n\n## Conclusion\n\nIn MTC 1.4.0, users can expect significant performance enhancements when direct migration is taken advantage of. The direct migration feature also grants the user more granular progress and error reporting back in the user interface to make it easier to debug what went wrong with the migration.\n"},"6247f16d-bed2-5828-a87b-e39c667c35cc":{"id":"6247f16d-bed2-5828-a87b-e39c667c35cc","title":"Konveyor Community HackFest","slug":"/konveyor-community-hackfest/","description":"Get free hands-on experience migrating different workload types to Kubernetes with open source tools and community engineer support.","tags":["HackFest"],"content":"---\nauthor: konveyor\ndate: 2021-12-21T07:00:00Z\ndescription: >-\n Get free hands-on experience migrating different workload types to Kubernetes with open source tools and community engineer support.\nfeatured: false\nimage: banner.jpg\ntags:\n - HackFest\ntitle: Konveyor Community HackFest\n---\n\n**January 31–February 4, 2022. 9 a.m.–5 p.m. EST each day**\n\nGet free hands-on experience migrating different workload types to Kubernetes with open source tools and community engineer support. [Register to get the calendar invite](https://docs.google.com/forms/d/1DGM5x8x4UyFAUQPkrJoVicnVWmovPbRqumLeotHtugI/edit?ts=61a8ce49).\n\nThe Konveyor community has developed multiple use cases for you to learn time- and cost-efficient ways to migrate to Kubernetes. During this HackFest, if something is missing, not working as expected, or you simply get stuck — you can open a GitHub issue or get support from the community engineers.\n\nBy joining, you’ll help improve the effectiveness and usability of the open source tools in the Konveyor Community. All tools you can continue to leverage for free after the event is over to migrate to Kubernetes.\n\n**You’ll walk away knowing how to:**\n\n- Rehost apps between Kubernetes clusters and automating with GitOps using the tool Crane\n\n- Replatform apps to Kubernetes from other container orchestration platforms with tool Move2Kube\n\n- Rehost virtual machines to KubeVirt with tool Forklift\n\n- Assess, analyze, and refactor applications to Kubernetes with tool Tackle.\n\nEach day will be dedicated to 1 or 2 use cases addressed by our tools. You can participate each day or the day we focus on the use case most relevant to you.\n\n[Register on this form](https://docs.google.com/forms/d/1DGM5x8x4UyFAUQPkrJoVicnVWmovPbRqumLeotHtugI/edit?ts=61a8ce49) to get the calendar invite and full agenda once it is finalized.\n\n- [Details on scenario and instructions](https://github.com/konveyor/hackathon)\n"},"66783370-91da-5d9a-adff-fbc3fe0fdf75":{"id":"66783370-91da-5d9a-adff-fbc3fe0fdf75","title":"Konveyor is now a Cloud Native Computing Foundation (CNCF) Sandbox project","slug":"/konveyor-is-a-cncf-sandbox-project/","description":"Big news! Konveyor was recently accepted as a Cloud Native Computing Foundation (CNCF) Sandbox project.","tags":["CNCF"],"content":"---\nauthor: konveyor\ndate: 2022-08-05T07:00:00Z\ndescription: >-\n Big news! Konveyor was recently accepted as a Cloud Native Computing Foundation (CNCF) Sandbox project.\nfeatured: true\nimage: konveyor-cncf.png\ntags:\n - CNCF\ntitle: Konveyor is now a Cloud Native Computing Foundation (CNCF) Sandbox project\n---\n\n**Big news! Konveyor was recently accepted as a Cloud Native Computing Foundation (CNCF) Sandbox project 🎉**\n\n## Why are we so excited about this?\n\nThis is a huge milestone in our mission to accelerate the movement of applications to run on Kubernetes with an open-source approach. With the added credibility of our sandbox status, we can more easily attract and convince others to adopt and contribute to Konveyor. The result will be more effective open source tools that everyone can use to adopt Kubernetes and cloud-native technology faster!\n\n## What happens now?\n\nWe’re trying to get the word out about our new status.\n\nWith regards to tools, we’re rethinking where to focus based on interest and usage. More on that to come later. For now, sharing the news with your network would be the most helpful.\n\nAnd lastly, thank you to all involved for helping this happen:\n\n- Karena Angell and Josh Berkus for guiding us through the application process.\n- IBM Research and Red Hat for contributing tools and helping to spread the word about the community.\n- Microsoft for contributing PRs and providing feedback to the community.\n- And to all of you on this email list for attending meetups, using the tools, giving us feedback, and spreading the word.\n\nHappy migrating,\n\nKonveyor team\n"},"b02029b7-a34d-5c9d-8560-48f70b6e2df1":{"id":"b02029b7-a34d-5c9d-8560-48f70b6e2df1","title":"A Method to Measure and Manage Technical Debt","slug":"/measure-manage-technical-debt/","description":"we demonstrate that not only is technical debt key to making decisions regarding any specific application, it is also important when attempting to prioritize work between multiple applications.","tags":["Metrics"],"content":"---\nauthor: ospaporta\ndate: 2022-07-07T07:00:00Z\ndescription: >-\n we demonstrate that not only is technical debt key to making decisions regarding any specific application, it is also important when attempting to prioritize work between multiple applications.\nfeatured: true\nimage: banner.jpg\ntags:\n - Metrics\ntitle: A Method to Measure and Manage Technical Debt\n---\n\nAs a software developer, technical debt is all those little things that you feel are hampering the efficiency of your coding. These are the issues that you (or your manager) choose to handle next time, because of the urgency of the current release. But sometimes, by the time you get to them, they have become so big you do not know where to start solving them. The difficult part is that decisions we make regarding technical debt have to balance between short term and long term implications of accumulating such debt, emphasizing the need to properly assess and address it when planning development cycles.\n\nIn their seminal article from 2012[^1], Nord et al suggest a metric to measure technical debt, based on dependencies between architectural elements. They use this method to show how an organization should plan development cycles while taking into account the effect the technical debt will have on the overall resources required for each subsequent version.\n\nIn this post, we demonstrate that not only is technical debt key to making decisions regarding any specific application, it is also important when attempting to prioritize work between multiple applications. Specifically, modernization work. Moreover, we show a method that can be used to not only compare the performance of different design paths for a single application, but also compare the technical debt levels of multiple applications at an arbitrary point in their development life cycle.\n\nThe main idea of the aforementioned article is to provide a way to measure technical debt. It is done using a formula that mainly relies on the dependencies between architectural elements in the given application. It is worth noting that the article does not define what constitutes an architectural element or how to identify these elements when approaching an application.\n\nWe took a similar approach and devised a method to measure technical debt of an application based on the dependency graph between its classes. The dependency graph is a directional graph _G_ =(_V_, _E_) in which the _V_ = {_c_1, _c_2, ...} is the set of all classes in the application and an edge _e_ = ⟨_c_1, _c_2⟩ ∈ _E_ exists between two vertices if class _c_1 depends on class _c_2 in the original code. We perform multi-faceted analysis on the graph to eventually come up with a score that describes the technical debt of the application. Here are some of the metrics we extract from the raw graph:\n\n1. Average/median outdegree of the vertices on the graph\n1. Top N outdegree of any node in the graph.\n1. Longest paths between classes\n\nUsing standard clustering algorithms on the graph, we identify communities of classes within the graph and measure additional metrics on them, such as:\n\n1. Average outdegree of the identified communities\n1. Longest paths between communities\n\nOur hypothesis is that using these generic metrics on the dependency graphs, we can identify architectural issues which represent real technical debt in the original code base. Moreover, by analyzing dependencies on these two levels, class and community, we give a broad interpretation of what an architectural element is in practice, without attempting to formally define it.\n\nTo test this method, we created a data set of over fifty applications from a variety of domains (online retail, financial, automotive, etc…) and extracted the aforementioned metrics from them. We used this data set in two ways. First, we correlated specific instances of high ranking occurrences of outdegrees and long paths with local issues in the code. For example, identifying god classes by their high outdegree[^2]. This proved efficient and increased our confidence level that this approach is valid in identifying local technical debt issues. The second approach was to try and provide a high level score that can be used not only to identify technical debt in a single application but to also be able to compare technical debt between applications, and to use it to help prioritize which should be addressed and how. To do that we introduced three indexes:\n\n1. Complexity — represents the effort required to add new features into the software.\n1. Risk — represents the potential risk that adding new features has on the stability of existing ones.\n1. Overall Debt — represents the overall amount of extra work required when attempting to add new features.\n\nWe manually analyzed the applications in our data set, also employing the expert knowledge of the architects in charge of actively developing them, and scored each application’s complexity, risk, and overall debt on a scale of 1-5. We used these benchmarks to train a machine learning model which correlates the values of the extracted metrics with the indexes and normalizes them to a score of 0-100. At this point, we can use this trained model to issue a score per index for any new application we encounter which allows us to analyze entire portfolios of applications, and compare them both to one another and to our pre-calculated benchmark. The following graph depicts a sample of 21 applications demonstrating the relationship between the aforementioned metrics.\n\n![Graph show Complexity vs. Risk](tech_debt.jpg)\n\nThe overall debt levels were then converted into currency units, depicting the level of investment required to add new functionality into the system, e.g. only $0.1 of every $1 of any investment will go into innovation due to architectural technical debt. This is intended to help organizations build a business case for handling and removing architectural technical debt from their applications.\n\nWe have shown a method to measure technical debt of an application based on the dependencies between its classes. We have successfully used this method to both identify local issues which cause technical debt as well as providing a global score, comparable between applications. By employing this method, organizations can successfully assess and manage the technical debt in their software which will lead to a better overall decision making process.\n\n---\n\n_**Bio:** Ori Saporta co-founded vFunction and serves as its Systems Architect. Prior to founding vFunction, Ori was the lead Systems Architect of WatchDox until its acquisition by Blackberry, where he continued to serve in the role of Distinguished Systems Architect. Prior to that, Ori was a Systems Architect at Israeli’s Intelligence Core Technology Unit (8200). Ori has a BSc in Computer Engineering from Tel-Aviv University and an MSc in Computer Science from the same institute for which his thesis subject was “Testing and Optimizing Data-Structure Implementations Under the RC11 Memory Model.\"_\n\n[^1]: Nord, Robert L., et al. \"In search of a metric for managing architectural technical debt.\" _2012 Joint Working IEEE/IFIP Conference on Software Architecture and European Conference on Software Architecture_. IEEE, 2012.\n[^2]: [Wikipedia: God object](https://en.wikipedia.org/wiki/God_object).\n"},"8fc56bbc-6d0e-5590-8abd-cce011fe89be":{"id":"8fc56bbc-6d0e-5590-8abd-cce011fe89be","title":"Exploring a Metrics-Driven Approach to Transformation","slug":"/metrics-driven-approach-to-transformation/","description":"When we started providing professional services around enterprise Kubernetes, it became clear we needed a program-level framework for adopting containers that spelled out the activities of multiple project teams.","tags":["Metrics","OpenShift"],"content":"---\nauthor: tquinn\ndate: 2021-03-03T07:00:00Z\ndescription: >-\n When we started providing professional services around enterprise Kubernetes, it became clear we needed a program-level framework for adopting containers that spelled out the activities of multiple project teams.\nfeatured: true\nimage: banner.jpg\ntags:\n - Metrics\n - OpenShift\ntitle: Exploring a Metrics-Driven Approach to Transformation\n---\n\nMy team has been working with organizations adopting containers, Kubernetes, and Red Hat OpenShift for more than three years now. When we started providing professional services around enterprise Kubernetes, it became clear we needed a program-level framework for adopting containers that spelled out the activities of multiple project teams. Some participants would be focused on container platform management and operations, some on continuous delivery, some on the application lifecycle, and others on cross-cutting process transformation.\n\nWe’ve had success using this framework to help customers rethink container adoption as less a matter of new technology implementation and more as an “organizational journey,” where people and process concerns are at least as important as the successful deployment of OpenShift clusters.\n\nOver time, we’ve realized the program framework is missing a guiding force that gets executive stakeholders engaged and can keep all participants focused on a consistent, meaningful set of objectives. Too often, we’ve seen IT and development managers concentrated on narrow, tactical objectives that don’t drive the big-picture, transformational needs of those enterprises. What we felt was lacking was a set of trackable and meaningful measures that could demonstrate progress to stakeholders in a more visible way.\n\nWe were very excited by the release of [Accelerate](https://www.infoq.com/articles/book-review-accelerate) by Dr. Nicole Forsgren, Jez Humble, and Gene Kim last year as the culmination of “a four-year research journey to investigate what capabilities and practices are important to accelerate the development and delivery of software, and, in turn, value to companies.” The authors, known for their work on Puppet Labs’ _State of DevOps_ reports and books like _Continuous Delivery_ and _The Phoenix Project_, were able to use survey data and statistical analysis to show relationships between specific capabilities/practices and organizational performance.\n\nOne of these capabilities, software delivery performance, should be of particular interest to organizations undergoing cloud adoption and/or the digital transformation. Forsgren and her co-authors showed a statistical link between software delivery performance and organization performance, including financial indicators like profitability, productivity, market share, and number of customers. Interestingly, the authors showed a link between software delivery performance and _non-commercial_ performance as well: things like product quality, customer satisfaction, and achieving mission goals.\n\nEqually important, the authors defined software delivery performance in a concrete, measurable way that can be used as indicators for a range of transformative practices and capabilities. They defined software delivery performance using four metrics: Lead Time, Deployment Frequency, Mean Time to Recovery, and Change Failure Rate, described below.\n\n![Software delivery metrics](metrics.png)\n\nFinally, the authors enumerated the various practices and capabilities that drive software delivery performance as measured this way: test automation, deployment automation, loosely coupled architecture, and monitoring, among others.\n\nWhat this means is that we have specific measures that adopters of container platforms (among other emerging technologies) can use to guide how the technology is adopted in ways that can lead to better organizational performance. And we have a set of practices that can be applied against this technology backdrop, using containers and container platform as accelerators of those practices when possible.\n\nThe focus for the authors is on global performance, not local optimization, and on “outcomes not output,” so the organization rewards activities that matter, rather than sheer volume of activity. This last point is crucial. In an [earlier post](https://blog.openshift.com/assessing-app-portfolios-for-onboarding-to-openshift/), I wrote about app onboarding to OpenShift. Taken to the extreme, a myopic focus on the percentage of the portfolio or number of apps migrated to X (containers, Kubernetes, OpenShift, AWS, “The Cloud”) is a focus on _outputs not outcomes_. It’s a measure that seems to indicate progress but does not directly determine the success of the cloud adoption program as a whole, success that must involve some wider notion of commercial or noncommercial performance.\n\nPut another way, cloud platforms do not automatically confer continuous delivery capabilities upon their adopters. They enable them. They accelerate them. But without changing the way we deliver software as an organization — the way we work — cloud technology (or any other newly introduced technology) will probably fail to match its promise.\n\nI will be writing more about how we put a metrics-based approach into practice with our customers in upcoming posts, starting with an update on how we’ve begun to capture these metrics in dashboards to keep stakeholders and project participants aligned to meaningful goals.\n"},"4817dd65-b2a5-5372-8087-33259eb8678c":{"id":"4817dd65-b2a5-5372-8087-33259eb8678c","title":"Modernize Petclinic App to Kubernetes Using Konveyor","slug":"/modernize-petclinic-to-k8s-using-konveyor/","description":"Konveyor aims to surface insights on applications at scale to empower enterprise users to make better-informed decisions related to modernization activities. This tutorial focuses on addressing edge case issues with Hazelcast during Kubernetes migration, emphasizing the benefits of creating custom rules and sharing knowledge to streamline future modernization efforts.","tags":["Konveyor","Kubernetes","AppModernization"],"content":"---\nauthor: savitharaghunathan\ndate: 2023-07-11\ndescription: >-\n Konveyor aims to surface insights on applications at scale to empower enterprise users to make better-informed decisions related to modernization activities. This tutorial focuses on addressing edge case issues with Hazelcast during Kubernetes migration, emphasizing the benefits of creating custom rules and sharing knowledge to streamline future modernization efforts.\nfeatured: true\nimage: header.png\ntags:\n - Konveyor\n - Kubernetes\n - AppModernization\ntitle: Modernize Petclinic App to Kubernetes Using Konveyor\n---\n\n**Author**: [Savitha Raghunathan](https://github.com/savitharaghunathan)\n\nKonveyor aims to surface insights on applications at scale to empower enterprise users to make better-informed decisions related to modernization activities. When it comes to migrating applications to Kubernetes (K8s), it's important to note that some applications can be ported without any major issues. However, there are certain edge cases where applications may encounter difficulties during the migration process. One such edge case we will focus on in this tutorial involves Hazelcast. Hazelcast is an open-source in-memory data grid that provides distributed caching and data synchronization capabilities. In this tutorial, we will use Hazelcast as the session backing store. During the migration of an application utilizing Hazelcast, some issues arise due to the distributed nature of Hazelcast and the dynamic nature of a Kubernetes environment. In this specific case, network connectivity and discovery issues impact the functionality of the petclinic application.\n\nTo tackle this challenge, the tutorial will not only guide you on how to identify and translate specific edge case issues into custom rules but also emphasize the long-term benefits of sharing this knowledge within the organization. By investing time and effort in creating custom rules for this particular application, you are laying the groundwork for future migrations and modernizations throughout the app portfolio. Once we have integrated these custom rules as targets with Konveyor, we will gain valuable insights that can be applied to other applications in the portfolio. This knowledge-sharing mechanism allows others in the organization to quickly recognize similar issues and provides a clear path for resolving them.\n\nWhile creating custom rules may require additional effort initially, the resulting knowledge base will serve as a valuable resource for scaling these efforts across teams. It's not just about solving the problem for one application; it's about empowering others in the organization to handle future modernizations and migrations more efficiently. By sharing the insights gained from Konveyor and the custom rules, you contribute to the overall growth of knowledge and shorten the learning curve for future projects.\n\n## Goals:\n\n* This example will explore the reasons behind the failed attempt to lift and shift the petclinic app to Kubernetes. \n* We will leverage the lessons learned from this experience to develop custom rules and a target. We will then use the custom target with the Konveyor Analyzer module to analyze the application.\n* By implementing the recommended changes identified in the preceding step, we will refactor and deploy the app to Kubernetes.\n\n\n## Background: \nThe [Petclinic app](https://github.com/konveyor/spring-framework-petclinic/tree/legacy) has been modified to replicate the behavior of a real-world enterprise application. In this updated version, Hazelcast is used as the backing store to handle anonymous users' sessions. The application leverages Spring Session management, which facilitates clustered sessions beyond the limitations of an application container-specific solution. Consequently, multiple instances of the Petclinic application can utilize a shared store for user sessions. In this example, the Petclinic application instances utilize Hazelcast as an HTTP session store, enabling the instances to share sessions. This setup guarantees uninterrupted user sessions even if an instance becomes unavailable.\n\n![Traditional setup](petclinic-trad.png)\n\n## Prerequisites \n* [EKS v1.25 or above](https://github.com/konveyor/hack_env_helpers/blob/main/aws/eks/README.md)\n* [Konveyor Operator](https://konveyor.github.io/konveyor/installation/) \n\n## Walkthrough:\nThis walkthrough has the following three parts,\n1. Lift and shift to Kubernetes\n2. Analyze the app using Konveyor custom rules \n3. Refactor and deploy to Kubernetes\n\n### Part 1: Lift and Shift to Kubernetes\n\nIn this section, we will take the [modified petclinic app](https://github.com/konveyor/spring-framework-petclinic/tree/legacy) and deploy it in a Kubernetes Cluster and explore the reasons why the user session wasn't replicated.\n\n1. Deploy the application to Kubernetes\n```\nkubectl apply -f https://raw.githubusercontent.com/konveyor/spring-framework-petclinic/legacy/petclinic-legacy.yaml\n```\n\n**_Note: Please edit the ingress annotations to suit your ingress provider. The above deployment uses ALB for ingress._**\n\n2. After deployment, check if the resources are available\n```\nkubectl -n petclinic-legacy get all,ing\n```\nThe output should resemble the following,\n```\n$ kubectl -n petclinic-legacy get all,ing\nNAME READY STATUS RESTARTS AGE\npod/petclinic-legacy-d854c89f5-cgfch 1/1 Running 0 82s\npod/petclinic-legacy-d854c89f5-j6b4l 1/1 Running 0 82s\npod/petclinic-legacy-d854c89f5-xw78q 1/1 Running 0 82s\n\nNAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE\nservice/petclinic-legacy ClusterIP 10.100.93.168 8080/TCP 82s\n\nNAME READY UP-TO-DATE AVAILABLE AGE\ndeployment.apps/petclinic-legacy 3/3 3 3 83s\n\nNAME DESIRED CURRENT READY AGE\nreplicaset.apps/petclinic-legacy-d854c89f5 3 3 3 83s\n\nNAME CLASS HOSTS ADDRESS PORTS AGE\ningress.networking.k8s.io/petclinic-legacy alb * k8s-petclini-petclini-20798acd3f-1994483574.us-east-1.elb.amazonaws.com 80 82s\n```\n\nOnce the ingress is available, access the application with the format `/petclinic`. eg: `http://k8s-petclini-petclini-20798acd3f-1994483574.us-east-1.elb.amazonaws.com/petclinic/`\n\nHere's the high-level view of the deployment,\n\n![Pictorial rep of the setup](petclinic-ak.png)\n\n3. Browse through the application. You will notice that the session data changes with every request.\n\n[Click here to watch the video for part 1 in action - Lift and Shift deployment of Petclinic to K8s](https://www.youtube.com/watch?v=PTQdMHqjZzU)\n\n\n### Why did the deployment fail? \n* Based on the information from pod logs, it appears that each pod in the Kubernetes cluster has its own Hazelcast cluster. This means that each instance of the application has its own session backing store, resulting in session inconsistency. As requests are served by different pods in a round-robin fashion, the session keeps changing, which can cause issues with session management and data synchronization.\n\n* The root cause of this problem seems to be a failure in the automatic member discovery feature of Hazelcast. The app relies on TCP/IP for member discovery, but the address specified in the application configuration is not accessible from the Kubernetes cluster. \n\n#### Solution\n\n* To fix this issue, updating the Hazelcast dependency to a version that is compatible with Kubernetes is recommended. \n* Furthermore, the discovery method implemented in the codebase is not performing as expected in the Kubernetes (K8s) environment. Since the app is configured to use embedded Hazelcast and the deployment is not a statefulset, it is not possible to predict the IP addresses of the pods to configure the TCP/IP discovery method. A possible solution would be to configure Multicast discovery but it requires a secure network environment due to the broadcasting of packets, allowing any member with the appropriate cluster name to join the cluster, which grants less control over the cluster. In the given scenario, it is recommended to utilize the Kubernetes discovery plugin for effective embedded Hazelcast cluster management.\n\n*Note: This is one of the many solutions that are applicable in this scenario. This example aims at walking through the troubleshooting process and converts the knowledge gained into custom rules for future app migrations*\n\n### Part 2: Analyze the Petclinic App using Konveyor Custom Rules\n\n##### Step 1\n* Based on the lessons learned from the previous section, let's develop custom rules that incorporate the identified issues and their corresponding solutions.\n\n```\n\n\n\n\t\n\t\t\n\t\t\tThis ruleset detects embedded hazelcast, which may be problematic\n\t\t\twhen migrating an application to a cloud environment.\n\t\t\n\t\t\n\t\t\t\n\t\t\t\n\t\t\n\n\t\t\n\n\t\tHazelcast\n\t\n\t\n\t\t\n\t\t\t\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\tMETHOD_CALL\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\tMETHOD_CALL\n\t\t\t\t\t\n\t\t\t\t\n\t\t\t\n\t\t\t\n\t\t\t\t\n\t\t\t\t\t Consider using Kubernetes specific configuration.\n\t\t\t\t\t\n\t\t\t\t\n\t\t\t\t\n\t\t\t\n\t\t\n\t\t\n\t\t\n\t\t\t\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\n\t\t\t\n\t\t\t\n\t\t\t\n\t\t\t\t\tThe project uses hazelcast with the version between 2.0.0 and less than 5.0.0. Please use hazelcast 5.0 or above. T\n\t\t\t\t\n\t\t\t\t\n\t\t\t\n\t\t\n\t\n\n```\n\n*Rule 1: hazelcast-cloud-readiness-hz001* :\nLooks for the discovery methods that are not working as expected in Kubernetes and suggest a solution that works in the Kubernetes environment.\n\n\n*Rule 2: hazelcast-cloud-readiness-hz002* :\nIf the Hazelcast dependency is between version 2.0 and 4.2.7, it advises upgrading the dependency to version 5.0.0 or above\n\n##### Step 2\n* Let's integrate these custom rules into the Konveyor UI, so that it is easily accessible during the application analysis phase.\n\na. Open the Konveyor UI and Navigate to the 'Administrator' view\nb. Click on the `Custom Migration Targets` link from the side navigation. \n![](customtargets.png)\nc. Click on the 'Create New' button in the upper right corner to open the `New Custom Target` wizard.\n* Download the custom rule from [here](https://gist.github.com/savitharaghunathan/8e743daa96fc8f23da511b95d44fc2b1) and save it with an extension '.windup.xml'. Upload the file to the wizard and click on create button.\n![](newcustomtarget.png)\nd. Once created, the custom target is ready to be used in the Analysis of the application.\n \n##### Step 3\n* Select the 'Migration' view and click on the 'Analysis' tab\n\na. Create an app entry called `petclinic` in the `Analysis` tab of the tackle ui. \n* Fill in the name of the application\n* Expand the source code and enter the following\n * Repository Type: Git\n * Source Repository: https://github.com/konveyor/spring-framework-petclinic.git/\n * Branch: legacy\n * Root path: /\n\n * Click on the `Create` button.\n\nb. Select the `petclinic` app and click on the `Analyze` button.\n\n* An application analysis wizard will open. \n\t* Select `Source Code` in the dropdown and click the `Next` button\n \n * In the `Set Targets` pane, select `Containerization` as well as 'Hazelcast Session Management' options and click `Next`\n ![](customtargetselection.png)\n\n * For scope, select `Application and internal dependencies only` \n * Keep the defaults in the Advanced section\n * Move to the `Review` pane, and click on the`Run` button\n ![](review.png)\n\n\n\nc. You will notice that the status of the app has been updated to `In Progess`. Wait until it changes to `Completed`.\n\nd. Expand the app, and click on the Analysis `Report` hyperlink\n ![](reportlink.png)\n\n\ne. Tackle Analysis dashboard gets opened in a new tab.\n ![](applicationlist.png)\n\n##### Step 4 \n* Click on the `spring-framework-petclinic` hyperlink and a dashboard gets displayed. Navigate to the `Issues` tab where you can explore the issues. Pay attention to the ones that are categorized as `Cloud Mandatory` as they have to be addressed for a successful migration to Kubernetes.\n![](issuelist.png)\n\n##### Step 5\n* Expand on `Embedded Hazelcast` and `Embedded Hazelcast dependencies` to view the issues. These are the result of the custom target we added in Step 2.\n![](issues.png)\n\n[Click here to watch the video for part 2 in action - Konveyor Analysis with custom rules](https://www.youtube.com/watch?v=YOlmajHAxUI)\n\n\n### Part 3: Refactor and deploy to Kubernetes\n\nBy integrating the custom rules into Konveyor, you are not only addressing the specific edge case issues in the Petclinic app but also preparing to tackle similar patterns across your portfolio of applications. Let's imagine that you have several other applications in your portfolio that exhibit similar patterns. With the custom rule integrated into Konveyor, other teams and developers within your organization will benefit from the knowledge you've shared. As they scan their applications using Konveyor with the custom rules, they will be able to identify similar issues. \n\nTo better understand the scenario, let's take a closer look at the original state of the Petclinic application code before the update. As we delved into the analysis process in part 2 of this tutorial, it became apparent that there were certain issues related to Hazelcast that needed attention. These issues were effectively flagged by the Konveyor Analysis module. In this part, we will address those issues in the petclinic app and deploy the refactored app to Kubernetes. \n\n* Let's apply the changes suggested in part 2 to the application. You can find the source code for the refactored app [here](https://github.com/konveyor/spring-framework-petclinic/tree/petclinic-kube)\n\n* Before deploying the app, let's add the required RBAC permissions that allow Hazelcast to talk to the K8s API\n\n```\nkubectl apply -f https://raw.githubusercontent.com/konveyor/spring-framework-petclinic/petclinic-kube/hazelcast-kube.yaml\n```\n\n* Deploy the refactored application\n\n```\nkubectl apply -f https://raw.githubusercontent.com/konveyor/spring-framework-petclinic/petclinic-kube/petclinic.yaml\n```\n\n* Obtain the ingress of the refactored app deployment using \n\n```\nkubectl get ing -n petclinic-kube\n```\nand access the app using the format `/petclinic`\n\n![Refactored App](petclinic-rk.png)\n\n* Navigate through the app and you will notice that the session data remains the same irrespective of the pod that is serving the request.\n\n[Click here to watch the video for part 3 in action - Refractor and Deploy to K8s](https://www.youtube.com/watch?v=mLJcynCYPR4)\n\n\n## Conclusion\n\n* Throughout this tutorial, we have explored the capabilities of Konveyor in delivering a comprehensive overview of issues, enabling effective planning. Moreover, Konveyor offers the ability to dive deep into each issue, down to the specific line number. This functionality empowers developers to swiftly address and resolve issues without wasting time on locating their occurrence within the codebase.\n* In addition, we have delved into the process of creating custom rules and custom targets, which proved invaluable for conducting thorough application analysis. By investing time in creating custom rules and integrating them into Konveyor, you are not only alleviating the burden of scanning and identifying issues for each application individually but also establishing a knowledge-sharing mechanism that enables other teams to recognize and resolve these concerns efficiently. This collaborative approach accelerates the modernization and migration process, ensuring a smoother transition for all applications within your portfolio. \n\n## Get involved in the Konveyor Community\n\nThe Konveyor project is actively seeking additional use cases and migration experiences to enhance the current set of rulesets. If you have valuable insights or experiences to share, we encourage you to join the Migration-experience User Group. To find out more about getting involved, please click [here]( https://github.com/konveyor/community/tree/main/ug-migration-experience)."},"2e114cb3-49b3-5774-a2bc-022542987a09":{"id":"2e114cb3-49b3-5774-a2bc-022542987a09","title":"Reflecting on Large-Scale Cloud-Native Modernizations at KubeCon 23","slug":"/reflecting-on-large-scale-cloud-native-modernizations-at-kubecon-23/","description":"Migrating large infrastructures from an on-premise, monolithic, traditional IT management approach to a modern cloud-native Kubernetes-based ecosystem is a daunting task. Christopher Nuland (Konveyor Ambassador) led a conversation with Jared Burk and Valentina Rodriguez Sosa, Red Hat; James Bench, Maximus\n about the different migrations they have completed and the challenges they experienced.","tags":["Konveyor","AppModernization","Kubernetes"],"content":"---\nauthor: Christopher Nuland and Valentina Rodriguez Sosa\ndate: 2023-05-26\ndescription: >-\n Migrating large infrastructures from an on-premise, monolithic, traditional IT management approach to a modern cloud-native Kubernetes-based ecosystem is a daunting task. Christopher Nuland (Konveyor Ambassador) led a conversation with Jared Burk and Valentina Rodriguez Sosa, Red Hat; James Bench, Maximus\n about the different migrations they have completed and the challenges they experienced.\nfeatured: true\nimage: panel_blog.png\ntags:\n - Konveyor\n - AppModernization\n - Kubernetes\ntitle: Reflecting on Large-Scale Cloud-Native Modernizations at KubeCon 23\n---\n\nMigrating large infrastructures from an on-premise, monolithic, traditional IT management approach\nto a modern cloud-native Kubernetes-based ecosystem is a daunting task. \nChristopher Nuland (Konveyor Ambassador) led a conversation with Jared Burk and Valentina Rodriguez Sosa, Red Hat; James Bench, Maximus \nabout the different migrations they have completed and the challenges they experienced. \n\nChris and Valentina summarized the key 6 takeaways that combined questions from the audience\nand a summary of the panel discussion held at the KubeCon 23 in AMSTERDAM.\n![Konveyor](panel_blog.png)\n\n\n## Knowing where to start:\nStarting with the proper process, the right people, and vision is critical for any organization that wants to implement change,\nwhether it is adopting new technology or any methodology. When thinking about modernization, \nit is important to start understanding the value that it can provide me, such as hardening security,\nreducing operational time and costs, and accelerating software development. \nConnecting these values with my organization's mission, vision, and values \nwill create the Why for this project and a compelling vision that the teams should be aware of. \nUnderstanding the why will help create motivation and commitment and reduce any friction between business priorities and modernization's value.\n\n## Create a plan:\nAlign your goals to create metrics to measure success. If cost reduction is one of the key goals of your modernization plan, \ncalculate operational and infrastructure costs before and after any migration.\n\n## Create a pilot project:\nCreating a pilot project before the large-scale migration will help reduce any concerns you and your organization\n might have about costs, risks, timeframes, and outcomes. If your concern is about costs, choose one of the most significant \n and most complex applications as a pilot to understand the level of complexity and amount of work that will end up as a cost for the migration project. \n You can add a set of pilot apps with each app having different characteristics, so you can look at different measures such as costs, and risks. \n After the pilot has been succeeded, take lessons learned and compare the metrics you created to ensure you obtain the value you were looking for. \n\n## Industry Compliance\nWhen planning a cloud-native migration, it's essential to have a thorough understanding of your organization's industry-specific compliance standards, \nsuch as HIPAA, NIST, and GDPR. This knowledge is particularly crucial when transitioning from an entirely on-premise system.\nIn these traditional environments, data protection and other compliance standards are often addressed through physical infrastructure and isolation strategies.\nThis approach can lead to a phenomenon known as 'data gravity', where some data must remain on-premise due to compliance constraints.\nConsequently, a hybrid cloud architecture becomes necessary, allowing critical integrations to stay on-premise.\nGrasping these intricacies and forming a strategic plan around them are key steps towards a smooth migration that maintains industry compliance. \nThis preparation paves the way for a flexible, scalable, and efficient cloud-native system that adheres to industry rules and regulations. \nA balanced approach like this is essential for successful cloud adoption and robust compliance management. \nTo prevent compliance issues from stalling your migration process, it's advisable to start understanding \nand addressing your compliance requirements early in the migration process. \nThis proactive approach will help ensure a seamless transition to the cloud.\n\n## Getting Organizational Buy-In\nSecuring organizational buy-in during a large-scale enterprise migration to a cloud-native k8s platform is crucial for the project's success. \nA typical obstacle to smooth transitions is the presence of siloed organizational structures, where information and processes are isolated, \ncausing difficulties in coordinating and unifying migration efforts. \nThese siloed operations can slow down the migration process, inhibit the efficient use of cloud functionalities, \nand even lead to costly delays. To overcome these challenges, buy-in should start at the highest levels of the organization, \nwith the CTO and CEO setting the strategic direction and demonstrating commitment. \nThe C-suite's endorsement enables a culture shift, fostering a more collaborative environment conducive to such a significant cloud-native transformation. \nFurthermore, their role extends to ensuring the allocation of appropriate resources and investment in upskilling to enable the organization \nfor the change needed for cloud-native transformation. \nThis top-down approach needs to cascade to individual contributors, including engineers, who will be integral in the technical aspects of the migration. \nThese individuals should understand and endorse the strategic benefits of the migration, and feel empowered to collaborate across different units. \nIn this way, the entire organization can work cohesively towards a successful migration, while reaping the many benefits that a cloud-native platform \ncan offer such as scalability, reliability, and cost efficiency.\n\n## Don’t reinvent the wheel\nWhen talking about migrations, patterns are critical from the applications to the methodologies and tooling. \nWe have seen cases where companies are trying to reinvent the wheel, leading to a significant spend of $$$, resources, \nand sometimes to the right solution for them. We recommend researching and getting involved with community and modernization experts,\n who can help you find the best path quickly and save costs for your organization. \n\nhttps://youtu.be/k-Pvzg9eosQ\n\nHelp improve the Konveyor project by sharing your application modernization problems and solutions [here](https://github.com/konveyor/community/tree/main/ug-migration-experience). \n\nYour learnings will be used to improve the Konveyor project and help ease others modernize.\n"},"4e64e691-2837-5176-9915-fa959f64450b":{"id":"4e64e691-2837-5176-9915-fa959f64450b","title":"Konveyor v0.2.1 Release Announcement","slug":"/release-announcement-0-2-1/","description":"Konveyor v0.2.1 Release Announcement","tags":["Konveyor","Kubernetes","AppModernization"],"content":"---\nauthor: savitharaghunathan\ndate: 2023-07-06\ndescription: >-\n Konveyor v0.2.1 Release Announcement\nfeatured: true\nimage: release-0-2-1.png\ntags:\n - Konveyor\n - Kubernetes\n - AppModernization\ntitle: Konveyor v0.2.1 Release Announcement\n---\nWe are thrilled to announce the release of Konveyor 0.2.1! This release supports various features, like migration waves, integration with Jira, and other valuable minor updates.\n\nKey Highlights of Konveyor 0.2.1:\n* Migration waves\n* Jira Integration\n* Minor improvements\n\n### Migration Waves:\nWe are excited to introduce a significant addition to the Konveyor project, aimed at providing enhanced value throughout the migration process. We recognized the need to address the planning aspect required to scale the migration process across entire application portfolio. When dealing with a large-scale portfolio containing hundreds or even thousands of applications, it becomes impractical to execute the migration process in one go. To tackle this challenge, we have introduced the ability for Konveyor to define migration waves, allowing for an iterative and manageable approach. By breaking down the portfolio into waves, we enable a more sophisticated process that in the future we expect will automate the calculation of these waves based on various criteria. This feature empowers users to scale adoption efforts effectively, ensuring a seamless and efficient migration experience.\n\n### Jira Integration:\nJira Integration is a significant development in response to a key concern raised by top managers involved in modernization and migration initiatives. Understanding the overall project progress is crucial, and recognizing that most organizations utilize their task management tools, we have enabled Konveyor to integrate seamlessly with these existing systems to leverage their capabilities. Our approach entails creating tasks or issues within the respective task/issue managers to represent the work associated with each application in the portfolio. Konveyor will then retrieve real-time information about the current status of each application, providing comprehensive project visibility. We have designed a flexible and adaptable integration layer, ensuring that it remains independent of any specific task/issue manager peculiarities on the Konveyor side. Jira is the first implementation, but others could come in the future with other popular issue managers like the ones available in GitHub and GitLab.\n\n### Minor improvements:\nThese enhancements aim to refine and enhance the overall user experience of our platform. Some of the notable improvements are:\n\n* ServiceMonitor for hub metrics: We have introduced ServiceMonitor functionality to capture and monitor hub metrics, providing valuable insights into the performance of your system.\n\n* Expose Hub metrics: With this update, we have exposed hub metrics, allowing users to access and utilize metrics for monitoring and analysis purposes.\n\n* Make Ingress Creation Optional: This update allows Ingress creation optional, providing flexibility and control over your deployment configurations.\n\n* Support for Amazon Load Balancer Ingress controller: Our platform now supports the Amazon Load Balancer Ingress controller, enabling Konveyor to be easily deployed on EKS clusters.\n\n* Provide openshift-oauth as an authentication option: As part of our ongoing efforts to enhance authentication capabilities, we now offer openshift-oauth as an additional authentication option, providing more choices to meet your specific requirements.\n\n* Make rwx_supported false by default: This feature removes the RWX dependency enabling Konveyor to work without RWX volume by default.\n\nThese minor improvements reflect our commitment to continuously refining and enhancing our platform to deliver an optimized and user-friendly experience. We value your feedback and encourage you to explore these enhancements as you leverage our latest release. You can install Konveyor 0.2.1 from [community operators](https://operatorhub.io/operator/konveyor-operator/konveyor-0.2/konveyor-operator.v0.2.1). If you encounter any issues or have suggestions for features, we encourage you to open an issue [here](https://github.com/konveyor/operator/issues/new).\n\nHappy Modernizing!\n"},"d5b87e59-70d9-5a8e-8d1e-ee0aff9d7dad":{"id":"d5b87e59-70d9-5a8e-8d1e-ee0aff9d7dad","title":"Tackle 2.1 release","slug":"/tackle-2-1-release/","description":"New features include a new report that gives details about the application data layer, easier CSV importing, bulk deletion of applications, and a more streamlined user experience.","tags":["Tackle"],"content":"---\nauthor: konveyor\ndate: 2022-09-14T07:00:00Z\ndescription: >-\n New features include a new report that gives details about the application data layer, easier CSV importing, bulk deletion of applications, and a more streamlined user experience.\nfeatured: true\nimage: tackle-2-1-release.png\ntags:\n - Tackle\ntitle: 'Tackle 2.1 release'\n---\n\nAfter the major milestone that [Tackle 2.0](/blog/tackle-2-new-capabilities/) represented, the community has continued gathering feedback from the field to further polish the feature set and provide value in the context of modernization, migration and adoption projects. This has led to Tackle 2.1, available now in [operatorhub.io](https://operatorhub.io/), a minor release that has been focused on stabilizing the project and providing a more streamlined user experience, while still delivering some new tooling. The new features include the following:\n\n- **Integration with the Tackle DiVA project:** New report available in the application analysis results providing detailed information about the application data layer, including an extensive inventory of transactions and accessed databases with detailed stack traces for each transaction.\n- **Automated creation of missing entities on CSV import:** Tags and Business Services are not required to exist in Tackle prior to the import anymore. This simplifies dealing with large CSV files and the import process overall.\n- **Bulk delete of applications:** Applications can now be deleted at bulk in the application inventory. 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This is essential to provide key insights that allow Architects leading these massive projects to make informed decisions, thus reducing risks and making the required effort measurable and predictable.\n\nThe following is a list of the exciting new features included in Tackle 2.0:\n\n- **Administrator perspective**: Dedicated perspective to manage tool-wide configuration, with a similar approach and design to the OpenShift Administrator Perspective.\n- **Enhanced RBAC**: Three new differentiated personas with different permissions — Administrator, Architect and Migrator\n- **Integration with repositories**: Full integration with source code (Git, Subversion) and binaries (Maven) repositories to automate the retrieval of applications for analysis.\n- **Credentials management**: Secure store for multiple credential types (source control, Maven settings files, proxy). Credentials are managed by Administrators and assigned by Architects to applications.\n- **Proxy integration**: HTTP and HTTPS proxy configuration can be managed in the Tackle UI.\n- **Analysis module**: Full integration with the Windup project to allow the execution of application analysis from the application inventory.\n- **Enhanced analysis modes**: Aside from source and binary analysis modes, now Tackle includes the Source + Dependencies mode that parses the POM file available in the source repository to gather dependencies from corporate or public artifact repositories, adding them to the scope of the analysis.\n- **Analysis scope selection**: Simplified user experience to configure the analysis scope, with the possibility to force the analysis of known Open Source libraries.\n- **Authless deployment**: Tackle can now be optionally deployed without Keycloak, allowing full unauthenticated admin access to the tool. This is especially useful when deploying the tool in resource constrained environments like local instances of Minikube, where only a single user would have access to it.\n- **Seamless upgrades**: Tackle lifecycle is now managed by a new operator with Capability Level II, allowing seamless upgrades between GA versions.\n\nI would like to take the chance to congratulate the engineering teams involved in the development of this new release of Tackle for making this major leap forward possible. Of course, this has to be extended as well to the UI/UX, QE and Documentation teams that made sure our tool is usable and reliable.\n\nMake sure you visit [the new official documentation website](https://konveyor.github.io/tackle2/) for Tackle 2 to get started with the tool. We will keep updating the documentation to make sure we cover all the use cases and scenarios in which Tackle can be used. 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We wanted to dig deeper into the specifics. To do so, Konveyor community contributor Red Hat sponsored a survey of 600 IT decision makers (ITDM), backend developers, and software architects in the US, UK, and English-speaking Asia-Pacific (APAC).","content":"---\ntitle: State of Application Modernization Report 2022\ndescription: >-\n Both anecdotes and past surveys tell us that organizations are modernizing their applications. We wanted to dig deeper into the specifics. To do so, Konveyor community contributor Red Hat sponsored a survey of 600 IT decision makers (ITDM), backend developers, and software architects in the US, UK, and English-speaking Asia-Pacific (APAC).\nbanner: report-22-banner.jpg\nshare_image: /images/report-22.jpg\n---\n\nimport MainCol from '../../components/main-col'\nimport SidebarTOC from '../../components/sidebar-toc'\n\n\n\n```toc\n#TOC will render here\n```\n\n\n\n\n\nby Gordon Haff\n\nBoth anecdotes and past surveys tell us that organizations are modernizing their applications. We wanted to dig deeper into the specifics. To do so, Konveyor community contributor Red Hat sponsored a survey of 600 IT decision makers (ITDM), backend developers, and software architects in the US, UK, and English-speaking Asia-Pacific (APAC). We surveyed these respondents, drawn from third-party databases, in October and November of 2021. Their companies had to have an internal app dev team and had to be using or planning to use hybrid cloud or multicloud as well as containers (the overwhelming majority were already using both). Here are some of the things they told us.\n\n## Modernization is happening quickly\n\n![Companies plan for more than half of their custom applications to be modernized within the next year.](modernization-plan.svg)\n\nWe sought out respondents who were modernizing or planning to modernize their custom apps in some manner, so it’s no surprise that everyone we surveyed is modernizing. What’s perhaps less expected is how quickly they’re planning to modernize. Companies are planning to modernize over half of their custom applications during the next year and over a quarter during the next six months. Only 20% expected the modernization to take more than two years.\n\nDoes that seem a bit… optimistic? It does. Indeed, as was something of a theme throughout this survey, developers were less confident than their ITDM and architect counterparts that modernization would be either quick or straightforward.\n\nThe barriers cited by respondents provide additional evidence that modernization projects won’t always be smooth sailing. All regions except the UK said that resistance to change was the top barrier—and in the UK it was still near the top. The fact that this is a cultural challenge far more than a technical one suggests that overcoming such a barrier may be difficult and require senior management buy-in. Other top barriers were related concerns like time constraints, cost and budget constraints, and lack of skilled resources. Skills shortages in particular are a common theme almost across the board when we conduct surveys about important IT initiatives.\n\nHowever, even if you think that a lot of modernization projects are likely to slip out, the data certainly points to an intent to rapidly modernize.\n\n## There’s no single app modernization strategy\n\n![Companies intend to replatform, refactor, or repurchase just over half of their custom legacy applications.](replatform-plan.svg)\n\nIn considering app modernization strategies, we presented survey respondents with six choices, the widely used six Rs. These are:\n\n- **Retire:** Sunset or decommission applications that are no longer needed\n- **Retain:** Leave critical applications as-is until refactoring is required\n- **Rehost:** Copy applications to a cloud (whether hosted or on-prem) with minimal changes, i.e. “lift and shift”\n- **Replatform:** Use a cloud migration to upgrade operating systems, databases, and other components as needed in order to cloud-enable applications without changing core application code or architecture\n- **Refactor:** Re-architect as cloud-native, for example, by containerizing workloads or moving them to a serverless architecture\n- **Repurchase:** Move from perpetual licenses to a Software-as-a-Service (SaaS) model\n\nThat’s quite the range of options and they’re all being used to significant degrees. Retire and retain were each about half as popular than the four other options — which each captured about 20% of the applications being modernized. The overall story is definitely about matching the application modernization strategy to a given workload and company need rather than there being a single dominant approach across companies.\n\nWe again see developers being more cautious or pessimistic about more aggressive modernization approaches; they were more likely to intend to rehost relative to ITDMs and architects. We sometimes hear about “resume-driven development,” whereby developers supposedly want to gain experience in new technologies, even if doing so increases complexity. However, the developers in our survey were more likely to favor lower risk and lower effort approaches.\n\nWe also found that refactoring, which is the most involved modernization approach, is almost always a two-step approach. 90% of those who plan to refactor any legacy apps intend to replatform them first.\n\n## The US is further along than others\n\n
                          \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
                          USUKAPAC
                          Unique Definitions of App ModernizationUsing microservices architecture in the cloudImproving CI/CDImproving CI/CD
                          Unique Reasons for App ModernizationDecrease costsDecrease costsImprove security improve customer experience
                          Unique Barriers\n
                            \n
                          • Difficulty determining the right approach
                            • \n
                          • Do no see the value of modernizing
                            • \n
                          \n                           		Have not faces any barriersHave not faced any barriers
                          Unique ChallengesDifficulty determining the right approachNo differentiating challengesNo differentiating challenges
                          Unique Success MeasuresDecreased costincreased customer satisfactionImproved security increased customer satisfaction
                          Legacy App StrategyMore likely to retire or retain applicationsMore likely to rehost or repurchase applicationsMost likely to rehost or repurchase applications
                          Unique App Modernization PrioritiesNo differentiating PrioritiesData/analytics/BI applications\n
                            \n
                          • Customer-facing applications
                            • \n
                          • Data/analytics/BI applications
                            • \n
                          \n
                          \n
                          \n\nWe don’t generally find striking differences between regions but we do sometimes see more subtle ones that form something of a pattern, as was the case here.\n\nIn this case, we see the US uniquely defining app modernization as “Using microservices architecture in the cloud” while the other two regions defined it as “Improving CI/CD.” This suggests that the US is further along in app modernization. Having a well-developed CI/CD pipeline is foundational to microservices and other cloud-native technology approaches.\n\nWe see something similar crop up with respect to barriers and challenges. The UK and APAC haven’t faced any barriers. It’s reasonable to assume that’s because they haven’t gotten far enough into the process yet. By contrast, the US is focused on the “Difficulty determining the right approach,” suggesting that they’re actively figuring out the best way to implement a modernization strategy across their application portfolio.\n\n## Increasing scalability and reliability trump cost reductions\n\n![Companies plan to measure success of application modernization base on increased reliability and increased scalability.](measurement-plan.svg)\n\nHow are companies going to measure the success of their application modernizations? Decreased costs are one factor. Costs always matter to at least some degree; ask anyone who has ever owned a budget. But increased reliability (especially in the US) and scalability were at the top of the list overall, with security high up as well.\n\nThis was a question that had significant regional differences. Improving security was a significantly higher-ranked measure in APAC than in other regions and even edged out increased scalability there. APAC was also much more likely to measure increased customer satisfaction—especially relative to the US.\n\n## AI/ML, data caching, and high performance computing on the upswing\n\n![More companies expect to have AI/ML software, data caching tools, and high performance computing workloads in place in the next 2 years.](ai-ml.svg)\n\nWhile traditional workloads such as web servers, business process applications, and databases are the most common today, they’re not where workload growth is expected to be over the next two years. That would be AI/ML software, data caching (think Redis), and high performance computing, which are expected to grow at least 20% during that period. Analytics falls in between the two groups both in terms of level of usage today and its expected rate of growth.\n\nThus, many new applications and application architectures are likely to be in emerging technology areas which include these high growth workloads. While most of the workloads were fairly consistent across regions, AI/ML in the US (68%) was markedly higher than in the UK (57%) which was higher than in APAC (43%).\n\n## Is there a public cloud backlash?\n\n![Companies expect a shift from public cloud toward private cloud deployment 2 years from now, especially in the UK and APAC.](private-cloud-shift.svg)\n\nThe overwhelming majority of the companies we surveyed run at least some of their production applications on a public cloud although a significant number also run on a private cloud—whether on-premise, off-premise, or both.\n\nThe most striking thing about these numbers though is where they’re headed. The 98% of companies that have at least some production workloads on a public cloud today is expected to drop ten points over the next two years to 88%. This drop is almost entirely attributable to the UK and APAC with the US dropping only one point. In APAC specifically, a full 26% of companies plan to stop using public clouds for production workloads; most of those workloads would appear to be going to off-premise private clouds which have a commensurately large expected increase.\n\nWhat’s going on? Are public clouds falling out of favor?\n\nThere’s some anecdotal evidence that data egress and a general lack of cost predictability have driven some companies to repatriate certain applications to private clouds. Furthermore, edge computing architectures distribute workloads so as to bring compute resources closer to data and user services. (Although they still often have a cloud component, whether on a public cloud or on-premise.)\n\nHowever, in the US, the percentage of companies with one or more production workloads on a public cloud is expected to stay essentially flat. This suggests that the significant expected shift in the UK and APAC numbers probably isn’t explained by cost and edge computing alone.\n\nBased on other surveys we’ve conducted, those other reasons may relate to data privacy, data security, and data sovereignty concerns. It’s not a stretch to imagine that these concerns might be heightened in the UK and APAC, especially in light of the fact that the three large global public cloud providers are all headquartered in the US.\n\nThe above notwithstanding, however, backlash is probably too strong a term. Rather, with 77% already having a hybrid cloud infrastructure, the results suggest that companies are just increasingly sophisticated in placing workloads on the best kind of infrastructure for the purpose rather than taking more of a one-size-fits-all approach.\n\n## Slide deck with all findings\n\n\n\n[State of application modernization 2022](https://www.slideshare.net/KonveyorIO/state-of-application-modernization-2022) from [Konveyor Community](https://www.slideshare.net/KonveyorIO)\n\n---\n\n_Gordon Haff is Technology Advocate at Red Hat where he works on emerging technology strategy; writes about tech, trends, and their business impact; and is a frequent speaker at customer and industry events. Among the topics he works on are edge, blockchain, AI, quantum, cloud-native platforms, and next-generation application architectures. His books include From Pots and Vats to Programs and Apps and How Open Source Ate Software. His current podcast is Innovate @ Open. Prior to Red Hat, as an industry analyst, Gordon wrote hundreds of research notes, was frequently quoted in major publications on a wide range of IT topics, and advised clients on product and marketing strategies._\n\n                          \n"},"12cda7c0-1878-5c73-9ed1-b19f21c3c3b5":{"id":"12cda7c0-1878-5c73-9ed1-b19f21c3c3b5","title":"Application Modernization Report Shows Need For Kubernetes-specific Migration Tooling","slug":"/application-modernization-report/","description":"In MTC 1.4.0, a new feature called Direct Migration is available that will yield significant time savings for most customers migrating persistent volumes and/or internal images.","tags":["Kubernetes"],"content":"---\nauthor: ghaff\ndate: 2022-03-09T07:00:00Z\ndescription: >-\n In MTC 1.4.0, a new feature called Direct Migration is available that will yield significant time savings for most customers migrating persistent volumes and/or internal images.\nfeatured: false\nimage: report-22-banner.jpg\ntags:\n - Kubernetes\ntitle: Application Modernization Report Shows Need For Kubernetes-specific Migration Tooling\n---\n\nKonveyor is a community of people passionate about helping others modernize and migrate their applications to the hybrid cloud by building tools, identifying patterns, and providing advice on how to break down monoliths, adopt containers, and embrace Kubernetes. To do so the Konveyor community is currently working on five projects to help users rehost, replatform, and refactor their applications to Kubernetes.\n\nWhile conversations with users and data from various sources gave us some visibility into how migrations were taking place, we wanted to inform our priorities with recent detailed data. To do so, Red Hat, a Konveyor community contributor, sponsored a survey of 600 IT decision makers, backend developers, and software architects in the US, UK, and English-speaking Asia-Pacific (APAC) to better understand the application modernization landscape.\n\nHere are some of the findings that relate to Konveyor and application modernization:\n\n## Application modernization is happening now\n\nIt’s clear that there is urgency to roll out migration tooling. Among those we surveyed, those who were migrating or planning to, we found that they plan to modernize over half of their custom applications during the next year and over a quarter during the next six months. Only 20% expected the modernization to take more than two years. It’s clear this is happening right now.\n\nThat said, it’s not all smooth sailing and this doesn’t happen overnight. While some regions haven’t progressed far enough in their application modernization journey to experience serious barriers, others (notably the US) report that choosing a straightforward approach can be challenging. Organizations have many options to choose from and each option presents varying levels of complexity.\n\n![Companies plan for more than half of their custom applications to be modernized within the next year.](modernization-plan.svg)\n\n## Motivators for modernizing existing applications to Kubernetes\n\nThe survey tells us modernization is mostly being driven by the need for reliability, scalability and security. Decreasing costs were also on the list but, as we frequently see in other surveys about technology adoption or change, it’s not the driving factor.\n\n![Most companies decide to modernize their applications to increase scalability or reliability. Companies in APAC also seek to improve security and customer experience, while those in the US and UK want to decrease costs.](increase-scalability.svg)\n\nKonveyor's tool suite can be used to help realize organization’s migration plans.\n\n![How migration strategies companies intend to use based on this survey map to the Konveyor Tool Suite.](map-to-konveyor.svg)\n\nThe Konveyor tool suite maps closely to the migration strategies companies intend to use based on this survey: rehosting, replatforming, and refactoring.\n\n![Companies intend to replatform, refactor, or repurchase just over half of their custom legacy applications.](replatform-plan.svg)\n\n## Rehost applications to cloud with Forklift and Crane\n\nRehosting (20% of total) involves copying applications to a cloud (whether hosted or on-prem) with minimal changes, i.e. “lift and shift.” This will be familiar to anyone with experience in virtualization early on when bare metal servers were often moved to a virtual machine (VM) for greater efficiency but with little or no changes to the software and with relatively modest operational changes.\n\nWhile rehosting doesn’t provide the same depth of benefits as replatforming or refactoring, it’s the first step in the right direction. Rehosting was the single most common approach\n**Forklift** and **Crane** are the relevant Konveyor projects here. Forklift is focused on migrating VMs to Kubernetes and provides the ability to migrate multiple VMs to KubeVirt with minimal downtime.\n\nCrane is a rehosting tool that meets a different use case. Crane helps organizations to migrate applications between Kubernetes clusters. There are many times when developers and operations teams want to migrate between older and newer versions of Kubernetes, evacuate a cluster, or migrate to different underlying infrastructure.\n\n## Replatforming applications with Move2Kube\n\nReplatforming (18% of total) is using a cloud migration to upgrade operating systems, databases, and other components as needed in order to cloud-enable applications without changing core application code or architecture. Think of it as “lift, tinker, and shift.”\n\nThis is effectively an intermediate step between just rehosting and refactoring. In fact, it’s often a stepping stone; the survey found that 90% of those planning to refactor their apps plan to replatform them first.\n\n**Move2Kube** is a Konveyor project that allows customers to replatform their applications to Kubernetes orchestrated platforms. One area where replatforming is taking place is in the consolidation of container orchestration platforms to Kubernetes.\n\nDue to this consolidation, the Move2Kube project was started to focus on accelerating the process of replatforming to Kubernetes from platforms such as Swarm and Cloud Foundry. This project translates existing artifacts to Kubernetes artifacts to speed up the process of being able to run applications on Kubernetes.\n\n## Refactoring applications with Tackle\n\nRefactoring (17%) is often viewed as the most challenging application modernization strategy but it's the one with the most long-term impact. Refactoring involves re-architecting as cloud-native, for example, by containerizing workloads, transforming a monolith to microservices, or moving functions to a serverless architecture.\n\nWhile **Tackle** is not a full refactoring tool, it provides a series of interrelated tools that allow users to assess, analyze, and ultimately move their applications onto a Kubernetes orchestrated platform.\n\n---\n\nAs you can see, organizations are taking a thoughtful approach to app migration and there’s no single right path. This data supports the Konveyor community’s approach of providing a toolbox, rather than just a singular tool, that can support transitioning applications however it is happening.\n"},"35c98cc0-f22c-58d0-b62d-48bcada7c94f":{"id":"35c98cc0-f22c-58d0-b62d-48bcada7c94f","title":"Community Update: Konveyor Refocuses Efforts on Replatforming and Refactoring Use Cases","slug":"/community-update-konveyor-refocuses-efforts/","description":"We recently revealed upcoming changes to the Konveyor Project. These adjustments are designed to solve the most important application modernizations problem better and to encourage participation with our community.","tags":["Crane","Forklift","Move2Kube","Pelorus","Tackle"],"content":"---\nauthor: konveyor\ndate: 2022-10-20T07:00:00Z\ndescription: >-\n We recently revealed upcoming changes to the Konveyor Project. These adjustments are designed to solve the most important application modernizations problem better and to encourage participation with our community.\nfeatured: true\nimage: banner.jpg\ntags:\n - Crane\n - Forklift\n - Move2Kube\n - Pelorus\n - Tackle\ntitle: 'Community Update: Konveyor Refocuses Efforts on Replatforming and Refactoring Use Cases'\n---\n\nIn the latest [community update](https://youtu.be/jyd3mpvVCC4), we revealed upcoming changes to the Konveyor Project. These adjustments are designed to solve the most important application modernizations problem better and to encourage participation with our community. Here’s what we announced:\n\n- We will solely focus on solving for the replatforming and refactoring use cases.\n- It’s easier to contribute and collaborate with Konveyor thanks to our new special interest group (SIG) model.\n- You can learn the Konveyor project, see upcoming features, and give us feedback at our workshop — part of the OpenShift Commons Gathering at KubeCon NA 2022. [Register for the Gathering](https://hopin.com/events/openshift-commons-gathering-2022-at-kubecon-na-detroit) to secure your spot.\n- Tackle 2.1 is available, future Tackle releases will be branded Konveyor.\n- Konveyor roadmap includes migration wave management, multi language support, and integrations with modernization tools.\n\nYou can get the details of each announcement below.\n\n## We are refocusing efforts on replatforming and refactoring use cases\n\nA key insight the [State of Application Modernization Report](/modernization-report/) surfaced is that users are more interested in replatforming and refactoring then just rehosting workloads or “lifting and shifting”. Paired with feedback from users, this revealed a gap in the tooling for refactoring which Konveyor is now addressing\n\nOriginally, Konveyor took a “big tent” approach to rehosting, replatforming and refactoring. We brought the tooling to a community of engineers, developers, and users to figure out what problems they need to solve. Now, due to their feedback, Konveyor is refocusing on just replatforming and refactoring, meaning:\n\n- Pelorus, Tackle and Move2Kube will be integrated and moved into a single project, now called Konveyor.\n- Crane (rehosting from one Kubernetes cluster to another) will be moved into a separate GitHub organization.\n- Forklift (rehosting to VMs) will move into a KubeVirt project focused on running VM’s with Kubernetes.\n\nCrane and Forklift will continue to exist but will no longer be part of the core Konveyor toolset.\n\n![Project changes: chart showing what will happen to each of the subprojects after the refocus.](project-changes.svg)\n\n## Special interest group (SIG) model makes it easier to contribute and collaborate with the project\n\nOne of the major changes to the Konveyor project is the refocusing on the major areas of code, UI, analyzers, and add-ons, each of which is represented by a special interest group (SIG) modeled after the SIGs created by the Kubernetes community. These groups are responsible for the development, integration, maintenance, and collaboration of the project.\n\nThe SIG Core is responsible for all of the core features of the Konveyor platform. These features include but are not limited to modernization, report generation, integration of program management tools, and the design of implementation of the hub itself.\n\nSIG UI is responsible for the user interface and experience across the platform. This SIG is also responsible for creating a pattern where all of the add-ons can be dynamically integrated into the hub.\n\nThe SIG Analyzers are working on creating an extensible pattern and standardization of input and output for the community to collaborate on the analyzers. The analyzers will each target specific programming languages.\n\nFinally SIG Add-ons are responsible for the development and integration of add-ons that will enhance Konveyor’s capabilities.\n\nThe community meetings bring together contributors and collaborators to provide a forum to discuss topics and new ideas and generate innovation, and happen on every first and third Thursday at 9 AM ET ([meetings are recorded](https://youtu.be/tiEJEiT8XtI)). Topics include milestones and features of upcoming releases, contributor showcases with member feedback. Above all, these meetings are intended to foster the community around Konveyor.\n\nThere are also many asynchronous opportunities to communicate and collaborate around Konveyor.\n\n- There is a #konveyor channel on the Kubernetes Slack channel. You can use it to ask any question about the project.\n- Contributors can subscribe to the [_Konveyor-community email list_](https://groups.google.com/u/0/g/konveyor-community) for community meeting invites and discussions to influence the direction of the community.\n- To get general updates, you can subscribe to the [email list](/community/#sign-up).\n- Or for more information, look at the Konveyor community repo — it includes information around governance documents, contributor letter, Get Started Guide, meeting agendas and developer notes.\n\n## Attend the Konveyor workshop at KubeCon North America 2022\n\nWe will run a workshop in the OpenShift Commons Gathering on 25 October, 2022. At this free, hands-on workshop, workshop leaders will take you through an assesment and analysis of a sample application using the Konveyor platform, followed by discussion of the Konveyor Roadmap and Q&A. Whether you are starting or continuing your application modernization journey, this is a great opportunity to learn how to contribute, or just how to use the tools. If you have any questions or just want to connect with the community or workshop, please reach out to Savita Raghunathan at [sraghuna@redhat.com](mailto:sraghuna@redhat.com) or on [Slack](/slack/).\n\n### How to register:\n\n- [Visit registration site](https://hopin.com/events/openshift-commons-gathering-2022-at-kubecon-na-detroit) and follow the directions below\n- Click \"register\"\n- Select \"Konveyor workshop\"\n- Click \"continue\"\n- Provide your info and submit\n\n## Tackle 2.1 is available, future Tackle releases will be branded Konveyor\n\nTackle 2.1 is available, with the ability to upgrade your current Tackle 2.0. Tackle 2.1 will be the final Tackle release. Future releases will bear the name Konveyor, and will begin with version 3.\n\nThe release of Konveyor 3 is envisioned for Q1 2023 pending the restructuring of the architecture, and some specific components to make contribution easier. For some of the more visionary components of Konveyor 4, the goal is to have these features ready for release in 2H 2023.\n\nIn Tackle 2.1 there are several important features:\n\nIntegration with [**DiVA** (_Data intensive Validity Advisor_)](https://github.com/konveyor/tackle-diva), which is now seamlessly integrated with Tackle: everything is available in the domain user interface to enable the new analysis mode. A transcription report tab is now included in analysis reports with detail on the data layer of your applications.\n\nThe next important feature is the ability to bulk delete applications. Before 2.1 it was possible to import applications in bulk, but not delete them. It will also include automated creation of missing entities on CSV import.\n\nNew rules will be included in the next patch to 2.1.1, allowing new migration paths for open JDK 11 to 17 rules, and with Microsoft as a new major player in the Konveyor community, migration to EAP and Spring Boot applications on top of Azure App Service is supported.\n\nFinally, the Konveyor community did a ton of bug fixing and optimization making this release much more stable than Tackle 2.0.\n\n## Konveyor roadmap\n\n![Diagram showing Konveyor roadmap for the next year](roadmap.svg)\n\nLooking forward to next year, several important features are visualized for the first release of Konveyor 3. First of these is **Migration Waves Management**. No one does a “big bang migration” when dealing with thousands of applications, but rather distributes application portfolio modernization across multiple waves. This new feature offers an assisted method for managing these waves, integrated into the main Konveyor user interface.\n\nFull integration with [**Tackle Test Generator**](https://github.com/konveyor/tackle-test-generator-cli) and [**Tackle Container Advisor**](https://github.com/konveyor/tackle-container-advisor#readme) in the main user interface is envisioned for this release as well. With Tackle Test Generator, tests for an application can be stored in your Git repository with a single click.\n\nTackle Container Advisor will leverage its’ entity standardization capability using the natural language description of the technology stack of the application, making it easier to ingest data at scale, simplifying CSV imports and Excel importing, and eliminating the need to code the technology stack as a series of separate tasks\n\n_Integration with Jira_ will allow the user to track and manage the whole migration process. Tackle will allow delegation of implementation to external issue managers or task managers. By creating issues in Jira related to the applications within the portfolio, a project leader can then assign them to developers to perform changes in the application portfolio.\n\n_Custom Migration Targets_ will be improved by abstracting users away from the complexities of having to assign custom rules without having to deal with these custom rules directly. Information and status on this feature should be available soon.\n\n_Custom rule upload_ to repositories will be integrated going forward to allow these rules to be uploaded automatically, and to be retrieved to and from source code repositories.\n\n_Tag management_ will also be improved, with numerous tags assigned to applications it is difficult for the UI to scale this information or consume it. This feature will help make these tags easier to consume.\n\nLooking even further into the future, Konveyor 4 will bring a whole new set of advanced features including multi language support for analysis, manifest generation and enhanced assessment module.\n\nEvery time Konveyor has been presented to an organization, invariably there is a request for multi language support. In an early prototype the Konveyor community has demonstrated the ability to use language server technology from Microsoft, decoupling the analysis from data models supporting analysis results. It’s very possible that this feature will be ready to ship with Konveyor 4 in May.\n\n_Manifest generation_ is another important feature: once you’ve successfully adapted source code to run on containers, this will then install the manifest on Kubernetes.\n\nFinally, feedback on the current **Assessment Module** is that it’s too opinionated, so the goal is to make it more intelligent and flexible.\n\nAltogether, the Konveyor Project has undergone a major transformation improving and simplifying, and creating new and better opportunities for building a community around Application Modernization centered around replatforming and refactoring.\n"},"54d9c5f1-8225-54fa-930c-37662b36595a":{"id":"54d9c5f1-8225-54fa-930c-37662b36595a","title":"Migrating Faster with Direct Migration","slug":"/direct-migration/","description":"In MTC 1.4.0, a new feature called Direct Migration is available that will yield significant time savings for most customers migrating persistent volumes and/or internal images.","tags":["MTC"],"content":"---\nauthor: dmurray\ndate: 2021-02-24T07:00:00Z\ndescription: >-\n In MTC 1.4.0, a new feature called Direct Migration is available that will yield significant time savings for most customers migrating persistent volumes and/or internal images.\nfeatured: false\nimage: banner.jpg\ntags:\n - MTC\ntitle: Migrating Faster with Direct Migration\n---\n\nIn MTC 1.4.0, a new feature called Direct Migration is available that will yield significant time savings for most customers migrating persistent volumes and/or internal images. Direct Migration enables the migration of persistent volumes and internal images directly from the source cluster to the destination cluster without an intermediary replication repository. This introduces a significant performance enhancement while also providing better error and progress reporting information back to the end-user.\n\nPrior MTC releases only allowed a 2 step backup and restore process when handling images and persistent volumes, which didn't take advantage of potential performance savings in the case of a migration with both the source and destination clusters having network connectivity. The prior process leveraged a filesystem copy tool called Restic integrated with Velero. MTC would need to copy PV and Image data twice: once from the source cluster to the replication repository, and a second time from the replication repository to the destination cluster. This process yielded flexibility for various environments, yet failed to take advantage of the more common case in a migration of direct network connectivity between clusters.\n\nWith Direct Migration in MTC 1.4, we are able to take advantage of any environments that have network connectivity between the clusters involved in the migration by handling the migration of PV data and Image data in a new way. Assuming remote clusters have exposed routes to enable external access to the internal registry, MTC will push internal images directly into the internal registry on the destination cluster from the source cluster. Assuming the clusters can communicate over port 443 via OpenShift routes, MTC will directly migrate Persistent Volume data from a source cluster to a destination cluster using a set of Rsync + Stunnel pods which we will describe more below.\n\n## Prerequisites\n\nAs mentioned above for direct image migrations, it is important for remote source and destination clusters internal registries be exposed for external network traffic.\n\n- [expose OCP 4 cluster registry](https://docs.openshift.com/container-platform/4.6/registry/securing-exposing-registry.html)\n- [expose OCP 3 cluser registry](https://docs.openshift.com/container-platform/3.11/install_config/registry/securing_and_exposing_registry.html)\n\nFor direct volume migrations, the source and destination clusters must be able to communicate over port 443 via OpenShift routes. MTC will create a route in each namespace to be migrated on the destination cluster and will be migrating the data by establishing an Rsync connection to this route. This means that the OpenShift routes must be accessible by the source cluster.\n\n![Configuration of 3 clusters running MTC](mtc-cluster.png)\n\nThe above diagram shows a configuration of 3 clusters running MTC. The Host cluster does not need to be its own cluster and could be the source or the destination cluster.\n\n## Direct Image Migration Details\n\nIn direct image migration (DIM), the Migration Controller pod creates a DIM resource that contains a list of namespaces to migrate. The DIM controller then finds all of the imagestreams with internal image references in those namespaces and copies them directly into the destination registry. In order for this to succeed, DIM also ensures the namespace exists on the destination cluster prior to the copy.\n\n![Clusters using DIM for migration](dim.png)\n\nThe above diagram shows how DIM orchestrates the migration of an imagestream backed by the internal registry directly from the source cluster to the destination cluster.\n\n## Direct Volume Migration Details\n\nFor Direct Volume Migration, or DVM, the DVM controller takes in a list of PVCs to migrate and performs a few steps prior to copying the data over. For DVM to work, it is necessary for the source and destination clusters to be able to communicate over port 443 via OCP routes which are created by DVM.\n\nFirst, DVM sets up the needed configuration configmaps and secrets across all the namespaces to migrate and then creates transfer pods on the destination cluster in each namespace to be migrated. The transfer pods on the destination include both rsyncd and stunnel containers. Stunnel is used to open up a communication tunnel between the source and destination. The rsyncd container has volume mounts to all PVCs in the namespace which are to be migrated. An rsync client pod is created on the source (1 per PVC) to then rsync the data via the stunnel route.\n\n![MTC orchestrating a direct migration](migrating.png)\n\nThe above diagram shows how MTC orchestrates a direct volume migration by standing up a set of rsync and stunnel pods to directly migrate the PV data from the source to the destination cluster.\n\n## Conclusion\n\nIn MTC 1.4.0, users can expect significant performance enhancements when direct migration is taken advantage of. The direct migration feature also grants the user more granular progress and error reporting back in the user interface to make it easier to debug what went wrong with the migration.\n"},"6247f16d-bed2-5828-a87b-e39c667c35cc":{"id":"6247f16d-bed2-5828-a87b-e39c667c35cc","title":"Konveyor Community HackFest","slug":"/konveyor-community-hackfest/","description":"Get free hands-on experience migrating different workload types to Kubernetes with open source tools and community engineer support.","tags":["HackFest"],"content":"---\nauthor: konveyor\ndate: 2021-12-21T07:00:00Z\ndescription: >-\n Get free hands-on experience migrating different workload types to Kubernetes with open source tools and community engineer support.\nfeatured: false\nimage: banner.jpg\ntags:\n - HackFest\ntitle: Konveyor Community HackFest\n---\n\n**January 31–February 4, 2022. 9 a.m.–5 p.m. EST each day**\n\nGet free hands-on experience migrating different workload types to Kubernetes with open source tools and community engineer support. [Register to get the calendar invite](https://docs.google.com/forms/d/1DGM5x8x4UyFAUQPkrJoVicnVWmovPbRqumLeotHtugI/edit?ts=61a8ce49).\n\nThe Konveyor community has developed multiple use cases for you to learn time- and cost-efficient ways to migrate to Kubernetes. During this HackFest, if something is missing, not working as expected, or you simply get stuck — you can open a GitHub issue or get support from the community engineers.\n\nBy joining, you’ll help improve the effectiveness and usability of the open source tools in the Konveyor Community. All tools you can continue to leverage for free after the event is over to migrate to Kubernetes.\n\n**You’ll walk away knowing how to:**\n\n- Rehost apps between Kubernetes clusters and automating with GitOps using the tool Crane\n\n- Replatform apps to Kubernetes from other container orchestration platforms with tool Move2Kube\n\n- Rehost virtual machines to KubeVirt with tool Forklift\n\n- Assess, analyze, and refactor applications to Kubernetes with tool Tackle.\n\nEach day will be dedicated to 1 or 2 use cases addressed by our tools. You can participate each day or the day we focus on the use case most relevant to you.\n\n[Register on this form](https://docs.google.com/forms/d/1DGM5x8x4UyFAUQPkrJoVicnVWmovPbRqumLeotHtugI/edit?ts=61a8ce49) to get the calendar invite and full agenda once it is finalized.\n\n- [Details on scenario and instructions](https://github.com/konveyor/hackathon)\n"},"66783370-91da-5d9a-adff-fbc3fe0fdf75":{"id":"66783370-91da-5d9a-adff-fbc3fe0fdf75","title":"Konveyor is now a Cloud Native Computing Foundation (CNCF) Sandbox project","slug":"/konveyor-is-a-cncf-sandbox-project/","description":"Big news! Konveyor was recently accepted as a Cloud Native Computing Foundation (CNCF) Sandbox project.","tags":["CNCF"],"content":"---\nauthor: konveyor\ndate: 2022-08-05T07:00:00Z\ndescription: >-\n Big news! Konveyor was recently accepted as a Cloud Native Computing Foundation (CNCF) Sandbox project.\nfeatured: true\nimage: konveyor-cncf.png\ntags:\n - CNCF\ntitle: Konveyor is now a Cloud Native Computing Foundation (CNCF) Sandbox project\n---\n\n**Big news! Konveyor was recently accepted as a Cloud Native Computing Foundation (CNCF) Sandbox project 🎉**\n\n## Why are we so excited about this?\n\nThis is a huge milestone in our mission to accelerate the movement of applications to run on Kubernetes with an open-source approach. With the added credibility of our sandbox status, we can more easily attract and convince others to adopt and contribute to Konveyor. The result will be more effective open source tools that everyone can use to adopt Kubernetes and cloud-native technology faster!\n\n## What happens now?\n\nWe’re trying to get the word out about our new status.\n\nWith regards to tools, we’re rethinking where to focus based on interest and usage. More on that to come later. For now, sharing the news with your network would be the most helpful.\n\nAnd lastly, thank you to all involved for helping this happen:\n\n- Karena Angell and Josh Berkus for guiding us through the application process.\n- IBM Research and Red Hat for contributing tools and helping to spread the word about the community.\n- Microsoft for contributing PRs and providing feedback to the community.\n- And to all of you on this email list for attending meetups, using the tools, giving us feedback, and spreading the word.\n\nHappy migrating,\n\nKonveyor team\n"},"b02029b7-a34d-5c9d-8560-48f70b6e2df1":{"id":"b02029b7-a34d-5c9d-8560-48f70b6e2df1","title":"A Method to Measure and Manage Technical Debt","slug":"/measure-manage-technical-debt/","description":"we demonstrate that not only is technical debt key to making decisions regarding any specific application, it is also important when attempting to prioritize work between multiple applications.","tags":["Metrics"],"content":"---\nauthor: ospaporta\ndate: 2022-07-07T07:00:00Z\ndescription: >-\n we demonstrate that not only is technical debt key to making decisions regarding any specific application, it is also important when attempting to prioritize work between multiple applications.\nfeatured: false\nimage: banner.jpg\ntags:\n - Metrics\ntitle: A Method to Measure and Manage Technical Debt\n---\n\nAs a software developer, technical debt is all those little things that you feel are hampering the efficiency of your coding. These are the issues that you (or your manager) choose to handle next time, because of the urgency of the current release. But sometimes, by the time you get to them, they have become so big you do not know where to start solving them. The difficult part is that decisions we make regarding technical debt have to balance between short term and long term implications of accumulating such debt, emphasizing the need to properly assess and address it when planning development cycles.\n\nIn their seminal article from 2012[^1], Nord et al suggest a metric to measure technical debt, based on dependencies between architectural elements. They use this method to show how an organization should plan development cycles while taking into account the effect the technical debt will have on the overall resources required for each subsequent version.\n\nIn this post, we demonstrate that not only is technical debt key to making decisions regarding any specific application, it is also important when attempting to prioritize work between multiple applications. Specifically, modernization work. Moreover, we show a method that can be used to not only compare the performance of different design paths for a single application, but also compare the technical debt levels of multiple applications at an arbitrary point in their development life cycle.\n\nThe main idea of the aforementioned article is to provide a way to measure technical debt. It is done using a formula that mainly relies on the dependencies between architectural elements in the given application. It is worth noting that the article does not define what constitutes an architectural element or how to identify these elements when approaching an application.\n\nWe took a similar approach and devised a method to measure technical debt of an application based on the dependency graph between its classes. The dependency graph is a directional graph _G_ =(_V_, _E_) in which the _V_ = {_c_1, _c_2, ...} is the set of all classes in the application and an edge _e_ = ⟨_c_1, _c_2⟩ ∈ _E_ exists between two vertices if class _c_1 depends on class _c_2 in the original code. We perform multi-faceted analysis on the graph to eventually come up with a score that describes the technical debt of the application. Here are some of the metrics we extract from the raw graph:\n\n1. Average/median outdegree of the vertices on the graph\n1. Top N outdegree of any node in the graph.\n1. Longest paths between classes\n\nUsing standard clustering algorithms on the graph, we identify communities of classes within the graph and measure additional metrics on them, such as:\n\n1. Average outdegree of the identified communities\n1. Longest paths between communities\n\nOur hypothesis is that using these generic metrics on the dependency graphs, we can identify architectural issues which represent real technical debt in the original code base. Moreover, by analyzing dependencies on these two levels, class and community, we give a broad interpretation of what an architectural element is in practice, without attempting to formally define it.\n\nTo test this method, we created a data set of over fifty applications from a variety of domains (online retail, financial, automotive, etc…) and extracted the aforementioned metrics from them. We used this data set in two ways. First, we correlated specific instances of high ranking occurrences of outdegrees and long paths with local issues in the code. For example, identifying god classes by their high outdegree[^2]. This proved efficient and increased our confidence level that this approach is valid in identifying local technical debt issues. The second approach was to try and provide a high level score that can be used not only to identify technical debt in a single application but to also be able to compare technical debt between applications, and to use it to help prioritize which should be addressed and how. To do that we introduced three indexes:\n\n1. Complexity — represents the effort required to add new features into the software.\n1. Risk — represents the potential risk that adding new features has on the stability of existing ones.\n1. Overall Debt — represents the overall amount of extra work required when attempting to add new features.\n\nWe manually analyzed the applications in our data set, also employing the expert knowledge of the architects in charge of actively developing them, and scored each application’s complexity, risk, and overall debt on a scale of 1-5. We used these benchmarks to train a machine learning model which correlates the values of the extracted metrics with the indexes and normalizes them to a score of 0-100. At this point, we can use this trained model to issue a score per index for any new application we encounter which allows us to analyze entire portfolios of applications, and compare them both to one another and to our pre-calculated benchmark. The following graph depicts a sample of 21 applications demonstrating the relationship between the aforementioned metrics.\n\n![Graph show Complexity vs. Risk](tech_debt.jpg)\n\nThe overall debt levels were then converted into currency units, depicting the level of investment required to add new functionality into the system, e.g. only $0.1 of every $1 of any investment will go into innovation due to architectural technical debt. This is intended to help organizations build a business case for handling and removing architectural technical debt from their applications.\n\nWe have shown a method to measure technical debt of an application based on the dependencies between its classes. We have successfully used this method to both identify local issues which cause technical debt as well as providing a global score, comparable between applications. By employing this method, organizations can successfully assess and manage the technical debt in their software which will lead to a better overall decision making process.\n\n---\n\n_**Bio:** Ori Saporta co-founded vFunction and serves as its Systems Architect. Prior to founding vFunction, Ori was the lead Systems Architect of WatchDox until its acquisition by Blackberry, where he continued to serve in the role of Distinguished Systems Architect. Prior to that, Ori was a Systems Architect at Israeli’s Intelligence Core Technology Unit (8200). Ori has a BSc in Computer Engineering from Tel-Aviv University and an MSc in Computer Science from the same institute for which his thesis subject was “Testing and Optimizing Data-Structure Implementations Under the RC11 Memory Model.\"_\n\n[^1]: Nord, Robert L., et al. \"In search of a metric for managing architectural technical debt.\" _2012 Joint Working IEEE/IFIP Conference on Software Architecture and European Conference on Software Architecture_. IEEE, 2012.\n[^2]: [Wikipedia: God object](https://en.wikipedia.org/wiki/God_object).\n"},"8fc56bbc-6d0e-5590-8abd-cce011fe89be":{"id":"8fc56bbc-6d0e-5590-8abd-cce011fe89be","title":"Exploring a Metrics-Driven Approach to Transformation","slug":"/metrics-driven-approach-to-transformation/","description":"When we started providing professional services around enterprise Kubernetes, it became clear we needed a program-level framework for adopting containers that spelled out the activities of multiple project teams.","tags":["Metrics","OpenShift"],"content":"---\nauthor: tquinn\ndate: 2021-03-03T07:00:00Z\ndescription: >-\n When we started providing professional services around enterprise Kubernetes, it became clear we needed a program-level framework for adopting containers that spelled out the activities of multiple project teams.\nfeatured: false\nimage: banner.jpg\ntags:\n - Metrics\n - OpenShift\ntitle: Exploring a Metrics-Driven Approach to Transformation\n---\n\nMy team has been working with organizations adopting containers, Kubernetes, and Red Hat OpenShift for more than three years now. When we started providing professional services around enterprise Kubernetes, it became clear we needed a program-level framework for adopting containers that spelled out the activities of multiple project teams. Some participants would be focused on container platform management and operations, some on continuous delivery, some on the application lifecycle, and others on cross-cutting process transformation.\n\nWe’ve had success using this framework to help customers rethink container adoption as less a matter of new technology implementation and more as an “organizational journey,” where people and process concerns are at least as important as the successful deployment of OpenShift clusters.\n\nOver time, we’ve realized the program framework is missing a guiding force that gets executive stakeholders engaged and can keep all participants focused on a consistent, meaningful set of objectives. Too often, we’ve seen IT and development managers concentrated on narrow, tactical objectives that don’t drive the big-picture, transformational needs of those enterprises. What we felt was lacking was a set of trackable and meaningful measures that could demonstrate progress to stakeholders in a more visible way.\n\nWe were very excited by the release of [Accelerate](https://www.infoq.com/articles/book-review-accelerate) by Dr. Nicole Forsgren, Jez Humble, and Gene Kim last year as the culmination of “a four-year research journey to investigate what capabilities and practices are important to accelerate the development and delivery of software, and, in turn, value to companies.” The authors, known for their work on Puppet Labs’ _State of DevOps_ reports and books like _Continuous Delivery_ and _The Phoenix Project_, were able to use survey data and statistical analysis to show relationships between specific capabilities/practices and organizational performance.\n\nOne of these capabilities, software delivery performance, should be of particular interest to organizations undergoing cloud adoption and/or the digital transformation. Forsgren and her co-authors showed a statistical link between software delivery performance and organization performance, including financial indicators like profitability, productivity, market share, and number of customers. Interestingly, the authors showed a link between software delivery performance and _non-commercial_ performance as well: things like product quality, customer satisfaction, and achieving mission goals.\n\nEqually important, the authors defined software delivery performance in a concrete, measurable way that can be used as indicators for a range of transformative practices and capabilities. They defined software delivery performance using four metrics: Lead Time, Deployment Frequency, Mean Time to Recovery, and Change Failure Rate, described below.\n\n![Software delivery metrics](metrics.png)\n\nFinally, the authors enumerated the various practices and capabilities that drive software delivery performance as measured this way: test automation, deployment automation, loosely coupled architecture, and monitoring, among others.\n\nWhat this means is that we have specific measures that adopters of container platforms (among other emerging technologies) can use to guide how the technology is adopted in ways that can lead to better organizational performance. And we have a set of practices that can be applied against this technology backdrop, using containers and container platform as accelerators of those practices when possible.\n\nThe focus for the authors is on global performance, not local optimization, and on “outcomes not output,” so the organization rewards activities that matter, rather than sheer volume of activity. This last point is crucial. In an [earlier post](https://blog.openshift.com/assessing-app-portfolios-for-onboarding-to-openshift/), I wrote about app onboarding to OpenShift. Taken to the extreme, a myopic focus on the percentage of the portfolio or number of apps migrated to X (containers, Kubernetes, OpenShift, AWS, “The Cloud”) is a focus on _outputs not outcomes_. It’s a measure that seems to indicate progress but does not directly determine the success of the cloud adoption program as a whole, success that must involve some wider notion of commercial or noncommercial performance.\n\nPut another way, cloud platforms do not automatically confer continuous delivery capabilities upon their adopters. They enable them. They accelerate them. But without changing the way we deliver software as an organization — the way we work — cloud technology (or any other newly introduced technology) will probably fail to match its promise.\n\nI will be writing more about how we put a metrics-based approach into practice with our customers in upcoming posts, starting with an update on how we’ve begun to capture these metrics in dashboards to keep stakeholders and project participants aligned to meaningful goals.\n"},"4817dd65-b2a5-5372-8087-33259eb8678c":{"id":"4817dd65-b2a5-5372-8087-33259eb8678c","title":"Modernize Petclinic App to Kubernetes Using Konveyor","slug":"/modernize-petclinic-to-k8s-using-konveyor/","description":"Konveyor aims to surface insights on applications at scale to empower enterprise users to make better-informed decisions related to modernization activities. This tutorial focuses on addressing edge case issues with Hazelcast during Kubernetes migration, emphasizing the benefits of creating custom rules and sharing knowledge to streamline future modernization efforts.","tags":["Konveyor","Kubernetes","AppModernization"],"content":"---\nauthor: savitharaghunathan\ndate: 2023-07-11\ndescription: >-\n Konveyor aims to surface insights on applications at scale to empower enterprise users to make better-informed decisions related to modernization activities. This tutorial focuses on addressing edge case issues with Hazelcast during Kubernetes migration, emphasizing the benefits of creating custom rules and sharing knowledge to streamline future modernization efforts.\nfeatured: true\nimage: header.png\ntags:\n - Konveyor\n - Kubernetes\n - AppModernization\ntitle: Modernize Petclinic App to Kubernetes Using Konveyor\n---\n\n**Author**: [Savitha Raghunathan](https://github.com/savitharaghunathan)\n\nKonveyor aims to surface insights on applications at scale to empower enterprise users to make better-informed decisions related to modernization activities. When it comes to migrating applications to Kubernetes (K8s), it's important to note that some applications can be ported without any major issues. However, there are certain edge cases where applications may encounter difficulties during the migration process. One such edge case we will focus on in this tutorial involves Hazelcast. Hazelcast is an open-source in-memory data grid that provides distributed caching and data synchronization capabilities. In this tutorial, we will use Hazelcast as the session backing store. During the migration of an application utilizing Hazelcast, some issues arise due to the distributed nature of Hazelcast and the dynamic nature of a Kubernetes environment. In this specific case, network connectivity and discovery issues impact the functionality of the petclinic application.\n\nTo tackle this challenge, the tutorial will not only guide you on how to identify and translate specific edge case issues into custom rules but also emphasize the long-term benefits of sharing this knowledge within the organization. By investing time and effort in creating custom rules for this particular application, you are laying the groundwork for future migrations and modernizations throughout the app portfolio. Once we have integrated these custom rules as targets with Konveyor, we will gain valuable insights that can be applied to other applications in the portfolio. This knowledge-sharing mechanism allows others in the organization to quickly recognize similar issues and provides a clear path for resolving them.\n\nWhile creating custom rules may require additional effort initially, the resulting knowledge base will serve as a valuable resource for scaling these efforts across teams. It's not just about solving the problem for one application; it's about empowering others in the organization to handle future modernizations and migrations more efficiently. By sharing the insights gained from Konveyor and the custom rules, you contribute to the overall growth of knowledge and shorten the learning curve for future projects.\n\n## Goals:\n\n* This example will explore the reasons behind the failed attempt to lift and shift the petclinic app to Kubernetes. \n* We will leverage the lessons learned from this experience to develop custom rules and a target. We will then use the custom target with the Konveyor Analyzer module to analyze the application.\n* By implementing the recommended changes identified in the preceding step, we will refactor and deploy the app to Kubernetes.\n\n\n## Background: \nThe [Petclinic app](https://github.com/konveyor/spring-framework-petclinic/tree/legacy) has been modified to replicate the behavior of a real-world enterprise application. In this updated version, Hazelcast is used as the backing store to handle anonymous users' sessions. The application leverages Spring Session management, which facilitates clustered sessions beyond the limitations of an application container-specific solution. Consequently, multiple instances of the Petclinic application can utilize a shared store for user sessions. In this example, the Petclinic application instances utilize Hazelcast as an HTTP session store, enabling the instances to share sessions. This setup guarantees uninterrupted user sessions even if an instance becomes unavailable.\n\n![Traditional setup](petclinic-trad.png)\n\n## Prerequisites \n* [EKS v1.25 or above](https://github.com/konveyor/hack_env_helpers/blob/main/aws/eks/README.md)\n* [Konveyor Operator](https://konveyor.github.io/konveyor/installation/) \n\n## Walkthrough:\nThis walkthrough has the following three parts,\n1. Lift and shift to Kubernetes\n2. Analyze the app using Konveyor custom rules \n3. Refactor and deploy to Kubernetes\n\n### Part 1: Lift and Shift to Kubernetes\n\nIn this section, we will take the [modified petclinic app](https://github.com/konveyor/spring-framework-petclinic/tree/legacy) and deploy it in a Kubernetes Cluster and explore the reasons why the user session wasn't replicated.\n\n1. Deploy the application to Kubernetes\n```\nkubectl apply -f https://raw.githubusercontent.com/konveyor/spring-framework-petclinic/legacy/petclinic-legacy.yaml\n```\n\n**_Note: Please edit the ingress annotations to suit your ingress provider. The above deployment uses ALB for ingress._**\n\n2. After deployment, check if the resources are available\n```\nkubectl -n petclinic-legacy get all,ing\n```\nThe output should resemble the following,\n```\n$ kubectl -n petclinic-legacy get all,ing\nNAME READY STATUS RESTARTS AGE\npod/petclinic-legacy-d854c89f5-cgfch 1/1 Running 0 82s\npod/petclinic-legacy-d854c89f5-j6b4l 1/1 Running 0 82s\npod/petclinic-legacy-d854c89f5-xw78q 1/1 Running 0 82s\n\nNAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE\nservice/petclinic-legacy ClusterIP 10.100.93.168 8080/TCP 82s\n\nNAME READY UP-TO-DATE AVAILABLE AGE\ndeployment.apps/petclinic-legacy 3/3 3 3 83s\n\nNAME DESIRED CURRENT READY AGE\nreplicaset.apps/petclinic-legacy-d854c89f5 3 3 3 83s\n\nNAME CLASS HOSTS ADDRESS PORTS AGE\ningress.networking.k8s.io/petclinic-legacy alb * k8s-petclini-petclini-20798acd3f-1994483574.us-east-1.elb.amazonaws.com 80 82s\n```\n\nOnce the ingress is available, access the application with the format `/petclinic`. eg: `http://k8s-petclini-petclini-20798acd3f-1994483574.us-east-1.elb.amazonaws.com/petclinic/`\n\nHere's the high-level view of the deployment,\n\n![Pictorial rep of the setup](petclinic-ak.png)\n\n3. Browse through the application. You will notice that the session data changes with every request.\n\n[Click here to watch the video for part 1 in action - Lift and Shift deployment of Petclinic to K8s](https://www.youtube.com/watch?v=PTQdMHqjZzU)\n\n\n### Why did the deployment fail? \n* Based on the information from pod logs, it appears that each pod in the Kubernetes cluster has its own Hazelcast cluster. This means that each instance of the application has its own session backing store, resulting in session inconsistency. As requests are served by different pods in a round-robin fashion, the session keeps changing, which can cause issues with session management and data synchronization.\n\n* The root cause of this problem seems to be a failure in the automatic member discovery feature of Hazelcast. The app relies on TCP/IP for member discovery, but the address specified in the application configuration is not accessible from the Kubernetes cluster. \n\n#### Solution\n\n* To fix this issue, updating the Hazelcast dependency to a version that is compatible with Kubernetes is recommended. \n* Furthermore, the discovery method implemented in the codebase is not performing as expected in the Kubernetes (K8s) environment. Since the app is configured to use embedded Hazelcast and the deployment is not a statefulset, it is not possible to predict the IP addresses of the pods to configure the TCP/IP discovery method. A possible solution would be to configure Multicast discovery but it requires a secure network environment due to the broadcasting of packets, allowing any member with the appropriate cluster name to join the cluster, which grants less control over the cluster. In the given scenario, it is recommended to utilize the Kubernetes discovery plugin for effective embedded Hazelcast cluster management.\n\n*Note: This is one of the many solutions that are applicable in this scenario. This example aims at walking through the troubleshooting process and converts the knowledge gained into custom rules for future app migrations*\n\n### Part 2: Analyze the Petclinic App using Konveyor Custom Rules\n\n##### Step 1\n* Based on the lessons learned from the previous section, let's develop custom rules that incorporate the identified issues and their corresponding solutions.\n\n```\n\n\n\n\t\n\t\t\n\t\t\tThis ruleset detects embedded hazelcast, which may be problematic\n\t\t\twhen migrating an application to a cloud environment.\n\t\t\n\t\t\n\t\t\t\n\t\t\t\n\t\t\n\n\t\t\n\n\t\tHazelcast\n\t\n\t\n\t\t\n\t\t\t\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\tMETHOD_CALL\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\tMETHOD_CALL\n\t\t\t\t\t\n\t\t\t\t\n\t\t\t\n\t\t\t\n\t\t\t\t\n\t\t\t\t\t Consider using Kubernetes specific configuration.\n\t\t\t\t\t\n\t\t\t\t\n\t\t\t\t\n\t\t\t\n\t\t\n\t\t\n\t\t\n\t\t\t\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\n\t\t\t\n\t\t\t\n\t\t\t\n\t\t\t\t\tThe project uses hazelcast with the version between 2.0.0 and less than 5.0.0. Please use hazelcast 5.0 or above. T\n\t\t\t\t\n\t\t\t\t\n\t\t\t\n\t\t\n\t\n\n```\n\n*Rule 1: hazelcast-cloud-readiness-hz001* :\nLooks for the discovery methods that are not working as expected in Kubernetes and suggest a solution that works in the Kubernetes environment.\n\n\n*Rule 2: hazelcast-cloud-readiness-hz002* :\nIf the Hazelcast dependency is between version 2.0 and 4.2.7, it advises upgrading the dependency to version 5.0.0 or above\n\n##### Step 2\n* Let's integrate these custom rules into the Konveyor UI, so that it is easily accessible during the application analysis phase.\n\na. Open the Konveyor UI and Navigate to the 'Administrator' view\nb. Click on the `Custom Migration Targets` link from the side navigation. \n![](customtargets.png)\nc. Click on the 'Create New' button in the upper right corner to open the `New Custom Target` wizard.\n* Download the custom rule from [here](https://gist.github.com/savitharaghunathan/8e743daa96fc8f23da511b95d44fc2b1) and save it with an extension '.windup.xml'. Upload the file to the wizard and click on create button.\n![](newcustomtarget.png)\nd. Once created, the custom target is ready to be used in the Analysis of the application.\n \n##### Step 3\n* Select the 'Migration' view and click on the 'Analysis' tab\n\na. Create an app entry called `petclinic` in the `Analysis` tab of the tackle ui. \n* Fill in the name of the application\n* Expand the source code and enter the following\n * Repository Type: Git\n * Source Repository: https://github.com/konveyor/spring-framework-petclinic.git/\n * Branch: legacy\n * Root path: /\n\n * Click on the `Create` button.\n\nb. Select the `petclinic` app and click on the `Analyze` button.\n\n* An application analysis wizard will open. \n\t* Select `Source Code` in the dropdown and click the `Next` button\n \n * In the `Set Targets` pane, select `Containerization` as well as 'Hazelcast Session Management' options and click `Next`\n ![](customtargetselection.png)\n\n * For scope, select `Application and internal dependencies only` \n * Keep the defaults in the Advanced section\n * Move to the `Review` pane, and click on the`Run` button\n ![](review.png)\n\n\n\nc. You will notice that the status of the app has been updated to `In Progess`. Wait until it changes to `Completed`.\n\nd. Expand the app, and click on the Analysis `Report` hyperlink\n ![](reportlink.png)\n\n\ne. Tackle Analysis dashboard gets opened in a new tab.\n ![](applicationlist.png)\n\n##### Step 4 \n* Click on the `spring-framework-petclinic` hyperlink and a dashboard gets displayed. Navigate to the `Issues` tab where you can explore the issues. Pay attention to the ones that are categorized as `Cloud Mandatory` as they have to be addressed for a successful migration to Kubernetes.\n![](issuelist.png)\n\n##### Step 5\n* Expand on `Embedded Hazelcast` and `Embedded Hazelcast dependencies` to view the issues. These are the result of the custom target we added in Step 2.\n![](issues.png)\n\n[Click here to watch the video for part 2 in action - Konveyor Analysis with custom rules](https://www.youtube.com/watch?v=YOlmajHAxUI)\n\n\n### Part 3: Refactor and deploy to Kubernetes\n\nBy integrating the custom rules into Konveyor, you are not only addressing the specific edge case issues in the Petclinic app but also preparing to tackle similar patterns across your portfolio of applications. Let's imagine that you have several other applications in your portfolio that exhibit similar patterns. With the custom rule integrated into Konveyor, other teams and developers within your organization will benefit from the knowledge you've shared. As they scan their applications using Konveyor with the custom rules, they will be able to identify similar issues. \n\nTo better understand the scenario, let's take a closer look at the original state of the Petclinic application code before the update. As we delved into the analysis process in part 2 of this tutorial, it became apparent that there were certain issues related to Hazelcast that needed attention. These issues were effectively flagged by the Konveyor Analysis module. In this part, we will address those issues in the petclinic app and deploy the refactored app to Kubernetes. \n\n* Let's apply the changes suggested in part 2 to the application. You can find the source code for the refactored app [here](https://github.com/konveyor/spring-framework-petclinic/tree/petclinic-kube)\n\n* Before deploying the app, let's add the required RBAC permissions that allow Hazelcast to talk to the K8s API\n\n```\nkubectl apply -f https://raw.githubusercontent.com/konveyor/spring-framework-petclinic/petclinic-kube/hazelcast-kube.yaml\n```\n\n* Deploy the refactored application\n\n```\nkubectl apply -f https://raw.githubusercontent.com/konveyor/spring-framework-petclinic/petclinic-kube/petclinic.yaml\n```\n\n* Obtain the ingress of the refactored app deployment using \n\n```\nkubectl get ing -n petclinic-kube\n```\nand access the app using the format `/petclinic`\n\n![Refactored App](petclinic-rk.png)\n\n* Navigate through the app and you will notice that the session data remains the same irrespective of the pod that is serving the request.\n\n[Click here to watch the video for part 3 in action - Refractor and Deploy to K8s](https://www.youtube.com/watch?v=mLJcynCYPR4)\n\n\n## Conclusion\n\n* Throughout this tutorial, we have explored the capabilities of Konveyor in delivering a comprehensive overview of issues, enabling effective planning. Moreover, Konveyor offers the ability to dive deep into each issue, down to the specific line number. This functionality empowers developers to swiftly address and resolve issues without wasting time on locating their occurrence within the codebase.\n* In addition, we have delved into the process of creating custom rules and custom targets, which proved invaluable for conducting thorough application analysis. By investing time in creating custom rules and integrating them into Konveyor, you are not only alleviating the burden of scanning and identifying issues for each application individually but also establishing a knowledge-sharing mechanism that enables other teams to recognize and resolve these concerns efficiently. This collaborative approach accelerates the modernization and migration process, ensuring a smoother transition for all applications within your portfolio. \n\n## Get involved in the Konveyor Community\n\nThe Konveyor project is actively seeking additional use cases and migration experiences to enhance the current set of rulesets. If you have valuable insights or experiences to share, we encourage you to join the Migration-experience User Group. To find out more about getting involved, please click [here]( https://github.com/konveyor/community/tree/main/ug-migration-experience)."},"bd209951-8e69-5576-a3a0-d112caaa67e5":{"id":"bd209951-8e69-5576-a3a0-d112caaa67e5","title":"One Year in the CNCF Sandbox- Konveyor's Reflective Journey","slug":"/one-year-cncf-sandbox-konveyor-reflective-journey/","description":"It has been an exceptional year for Konveyor since its admission into the CNCF in July 2022. Since then, the project has undergone a series of transformative changes and remarkable achievements, guided by a newly updated charter that has refocused Konveyor's mission towards refactoring and replatforming legacy applications. In this post, we invite you to join us on a journey down memory lane as we celebrate the numerous milestones, both big and small, that our dedicated contributors have accomplished over the past year.","tags":["Konveyor","Kubernetes","AppModernization"],"content":"---\nauthor: savitharaghunathan\ndate: 2023-09-21\ndescription: >-\n It has been an exceptional year for Konveyor since its admission into the CNCF in July 2022. Since then, the project has undergone a series of transformative changes and remarkable achievements, guided by a newly updated charter that has refocused Konveyor's mission towards refactoring and replatforming legacy applications. In this post, we invite you to join us on a journey down memory lane as we celebrate the numerous milestones, both big and small, that our dedicated contributors have accomplished over the past year.\nfeatured: true\nimage: header.png\ntags:\n - Konveyor\n - Kubernetes\n - AppModernization\ntitle: One Year in the CNCF Sandbox- Konveyor's Reflective Journey\n---\n\n**Author**: [Savitha Raghunathan](https://github.com/savitharaghunathan)\n\nIt has been an exceptional year for Konveyor since its admission into the CNCF in July 2022. Since then, the project has undergone a series of transformative changes and remarkable achievements, guided by a newly [updated charter](https://github.com/konveyor/community/blob/main/Charter.md) that has refocused Konveyor's mission towards refactoring and replatforming legacy applications. In this post, we invite you to join us on a journey down memory lane as we celebrate the numerous milestones, both big and small, that our dedicated contributors have accomplished over the past year.\n\nIn the initial months following Konveyor's acceptance into the CNCF sandbox, considerable effort was invested in establishing essential contributor documentation, forming a steering committee, and embracing best practices for repository management. We extend our heartfelt gratitude to [Josh Berkus](http://berkus.org/) and [Lenka Bočincová](https://www.linkedin.com/in/lenka-bočincová-0602a493/) from Red Hat OSPO for their invaluable guidance in onboarding Konveyor into the CNCF. [CNCF TAG-Contribex](https://github.com/cncf/tag-contributor-strategy) has developed [project templates](https://contribute.cncf.io/maintainers/templates/) that played a vital role in expediting our onboarding process. These templates encompassed everything from code of conduct to vulnerability management, demonstrating the thoughtful process of the TAG-Contribex team in helping project maintainers onboard easily. \n\nWith the revised charter, Konveyor's mission has now evolved to \"Accelerate the adoption of Kubernetes by assisting organizations in modernizing their legacy applications with Kubernetes and cloud-native technologies in a secure and predictable manner at scale, delivering value at every stage of the adoption journey.\" The project's future vision is encapsulated in the [Unified Experience](https://github.com/konveyor/enhancements/tree/master/enhancements/unified_experience), which serves as our guiding light for all development efforts. The evolution of Konveyor's roadmap is clearly evident, commencing with the initial emphasis on surfacing information in its 0.1 release. Subsequent release 0.2, extended this focus to enable the planning of work in the form of migration waves, culminating in a significant milestone in 0.3 - a comprehensive rewrite of the analysis engine. This rewrite is built upon the Language Server Protocol, laying the foundation for multi-language analysis capabilities. Currently, this feature supports Java and Go, with active development underway to extend this support to .NET/C#.\n\nWe are excited to share that [Claranet](https://claranet.com) is the latest contributor and community supporter of Konveyor. Their collaboration has been invaluable, as they have shared their extensive migration experience and knowledge, greatly enhancing the assessment of applications within the project. Claranet has introduced [the Konveyor Add-On for Amazon EKS Blueprints](https://github.com/claranet-ch/konveyor-eks-blueprint-addon), and they have also [packaged Konveyor for effortless deployment on AWS](https://aws.amazon.com/marketplace/pp/prodview-3pur2yyywakts), simplifying the onboarding process for organizations embarking on their modernization journey. If you have migration experiences to share, we encourage you to join the [Konveyor community meetings](https://github.com/konveyor/community#konveyor-community-meetings).\n\nFor the stats enthusiasts among us, here are some interesting metrics from the past year:\n\n* New Contributors: 38\n* Pull Requests: 2.44K\n* Issues Addressed: 903\n* Total Contributions: 21.7K\n* Commits: 3.9K\n\nAs we reflect on the remarkable progress achieved over the past year, we want to express our heartfelt gratitude to our contributors and supporters. It is your dedication and support that have made these achievements possible. We look forward to another year of growth, collaboration, and success in the Konveyor project.\n"},"2e114cb3-49b3-5774-a2bc-022542987a09":{"id":"2e114cb3-49b3-5774-a2bc-022542987a09","title":"Reflecting on Large-Scale Cloud-Native Modernizations at KubeCon 23","slug":"/reflecting-on-large-scale-cloud-native-modernizations-at-kubecon-23/","description":"Migrating large infrastructures from an on-premise, monolithic, traditional IT management approach to a modern cloud-native Kubernetes-based ecosystem is a daunting task. Christopher Nuland (Konveyor Ambassador) led a conversation with Jared Burk and Valentina Rodriguez Sosa, Red Hat; James Bench, Maximus\n about the different migrations they have completed and the challenges they experienced.","tags":["Konveyor","AppModernization","Kubernetes"],"content":"---\nauthor: Christopher Nuland and Valentina Rodriguez Sosa\ndate: 2023-05-26\ndescription: >-\n Migrating large infrastructures from an on-premise, monolithic, traditional IT management approach to a modern cloud-native Kubernetes-based ecosystem is a daunting task. Christopher Nuland (Konveyor Ambassador) led a conversation with Jared Burk and Valentina Rodriguez Sosa, Red Hat; James Bench, Maximus\n about the different migrations they have completed and the challenges they experienced.\nfeatured: true\nimage: panel_blog.png\ntags:\n - Konveyor\n - AppModernization\n - Kubernetes\ntitle: Reflecting on Large-Scale Cloud-Native Modernizations at KubeCon 23\n---\n\nMigrating large infrastructures from an on-premise, monolithic, traditional IT management approach\nto a modern cloud-native Kubernetes-based ecosystem is a daunting task. \nChristopher Nuland (Konveyor Ambassador) led a conversation with Jared Burk and Valentina Rodriguez Sosa, Red Hat; James Bench, Maximus \nabout the different migrations they have completed and the challenges they experienced. \n\nChris and Valentina summarized the key 6 takeaways that combined questions from the audience\nand a summary of the panel discussion held at the KubeCon 23 in AMSTERDAM.\n![Konveyor](panel_blog.png)\n\n\n## Knowing where to start:\nStarting with the proper process, the right people, and vision is critical for any organization that wants to implement change,\nwhether it is adopting new technology or any methodology. When thinking about modernization, \nit is important to start understanding the value that it can provide me, such as hardening security,\nreducing operational time and costs, and accelerating software development. \nConnecting these values with my organization's mission, vision, and values \nwill create the Why for this project and a compelling vision that the teams should be aware of. \nUnderstanding the why will help create motivation and commitment and reduce any friction between business priorities and modernization's value.\n\n## Create a plan:\nAlign your goals to create metrics to measure success. If cost reduction is one of the key goals of your modernization plan, \ncalculate operational and infrastructure costs before and after any migration.\n\n## Create a pilot project:\nCreating a pilot project before the large-scale migration will help reduce any concerns you and your organization\n might have about costs, risks, timeframes, and outcomes. If your concern is about costs, choose one of the most significant \n and most complex applications as a pilot to understand the level of complexity and amount of work that will end up as a cost for the migration project. \n You can add a set of pilot apps with each app having different characteristics, so you can look at different measures such as costs, and risks. \n After the pilot has been succeeded, take lessons learned and compare the metrics you created to ensure you obtain the value you were looking for. \n\n## Industry Compliance\nWhen planning a cloud-native migration, it's essential to have a thorough understanding of your organization's industry-specific compliance standards, \nsuch as HIPAA, NIST, and GDPR. This knowledge is particularly crucial when transitioning from an entirely on-premise system.\nIn these traditional environments, data protection and other compliance standards are often addressed through physical infrastructure and isolation strategies.\nThis approach can lead to a phenomenon known as 'data gravity', where some data must remain on-premise due to compliance constraints.\nConsequently, a hybrid cloud architecture becomes necessary, allowing critical integrations to stay on-premise.\nGrasping these intricacies and forming a strategic plan around them are key steps towards a smooth migration that maintains industry compliance. \nThis preparation paves the way for a flexible, scalable, and efficient cloud-native system that adheres to industry rules and regulations. \nA balanced approach like this is essential for successful cloud adoption and robust compliance management. \nTo prevent compliance issues from stalling your migration process, it's advisable to start understanding \nand addressing your compliance requirements early in the migration process. \nThis proactive approach will help ensure a seamless transition to the cloud.\n\n## Getting Organizational Buy-In\nSecuring organizational buy-in during a large-scale enterprise migration to a cloud-native k8s platform is crucial for the project's success. \nA typical obstacle to smooth transitions is the presence of siloed organizational structures, where information and processes are isolated, \ncausing difficulties in coordinating and unifying migration efforts. \nThese siloed operations can slow down the migration process, inhibit the efficient use of cloud functionalities, \nand even lead to costly delays. To overcome these challenges, buy-in should start at the highest levels of the organization, \nwith the CTO and CEO setting the strategic direction and demonstrating commitment. \nThe C-suite's endorsement enables a culture shift, fostering a more collaborative environment conducive to such a significant cloud-native transformation. \nFurthermore, their role extends to ensuring the allocation of appropriate resources and investment in upskilling to enable the organization \nfor the change needed for cloud-native transformation. \nThis top-down approach needs to cascade to individual contributors, including engineers, who will be integral in the technical aspects of the migration. \nThese individuals should understand and endorse the strategic benefits of the migration, and feel empowered to collaborate across different units. \nIn this way, the entire organization can work cohesively towards a successful migration, while reaping the many benefits that a cloud-native platform \ncan offer such as scalability, reliability, and cost efficiency.\n\n## Don’t reinvent the wheel\nWhen talking about migrations, patterns are critical from the applications to the methodologies and tooling. \nWe have seen cases where companies are trying to reinvent the wheel, leading to a significant spend of $$$, resources, \nand sometimes to the right solution for them. We recommend researching and getting involved with community and modernization experts,\n who can help you find the best path quickly and save costs for your organization. \n\nhttps://youtu.be/k-Pvzg9eosQ\n\nHelp improve the Konveyor project by sharing your application modernization problems and solutions [here](https://github.com/konveyor/community/tree/main/ug-migration-experience). \n\nYour learnings will be used to improve the Konveyor project and help ease others modernize.\n"},"4e64e691-2837-5176-9915-fa959f64450b":{"id":"4e64e691-2837-5176-9915-fa959f64450b","title":"Konveyor v0.2.1 Release Announcement","slug":"/release-announcement-0-2-1/","description":"Konveyor v0.2.1 Release Announcement","tags":["Konveyor","Kubernetes","AppModernization"],"content":"---\nauthor: savitharaghunathan\ndate: 2023-07-06\ndescription: >-\n Konveyor v0.2.1 Release Announcement\nfeatured: true\nimage: release-0-2-1.png\ntags:\n - Konveyor\n - Kubernetes\n - AppModernization\ntitle: Konveyor v0.2.1 Release Announcement\n---\nWe are thrilled to announce the release of Konveyor 0.2.1! This release supports various features, like migration waves, integration with Jira, and other valuable minor updates.\n\nKey Highlights of Konveyor 0.2.1:\n* Migration waves\n* Jira Integration\n* Minor improvements\n\n### Migration Waves:\nWe are excited to introduce a significant addition to the Konveyor project, aimed at providing enhanced value throughout the migration process. We recognized the need to address the planning aspect required to scale the migration process across entire application portfolio. When dealing with a large-scale portfolio containing hundreds or even thousands of applications, it becomes impractical to execute the migration process in one go. To tackle this challenge, we have introduced the ability for Konveyor to define migration waves, allowing for an iterative and manageable approach. By breaking down the portfolio into waves, we enable a more sophisticated process that in the future we expect will automate the calculation of these waves based on various criteria. This feature empowers users to scale adoption efforts effectively, ensuring a seamless and efficient migration experience.\n\n### Jira Integration:\nJira Integration is a significant development in response to a key concern raised by top managers involved in modernization and migration initiatives. Understanding the overall project progress is crucial, and recognizing that most organizations utilize their task management tools, we have enabled Konveyor to integrate seamlessly with these existing systems to leverage their capabilities. Our approach entails creating tasks or issues within the respective task/issue managers to represent the work associated with each application in the portfolio. Konveyor will then retrieve real-time information about the current status of each application, providing comprehensive project visibility. We have designed a flexible and adaptable integration layer, ensuring that it remains independent of any specific task/issue manager peculiarities on the Konveyor side. Jira is the first implementation, but others could come in the future with other popular issue managers like the ones available in GitHub and GitLab.\n\n### Minor improvements:\nThese enhancements aim to refine and enhance the overall user experience of our platform. Some of the notable improvements are:\n\n* ServiceMonitor for hub metrics: We have introduced ServiceMonitor functionality to capture and monitor hub metrics, providing valuable insights into the performance of your system.\n\n* Expose Hub metrics: With this update, we have exposed hub metrics, allowing users to access and utilize metrics for monitoring and analysis purposes.\n\n* Make Ingress Creation Optional: This update allows Ingress creation optional, providing flexibility and control over your deployment configurations.\n\n* Support for Amazon Load Balancer Ingress controller: Our platform now supports the Amazon Load Balancer Ingress controller, enabling Konveyor to be easily deployed on EKS clusters.\n\n* Provide openshift-oauth as an authentication option: As part of our ongoing efforts to enhance authentication capabilities, we now offer openshift-oauth as an additional authentication option, providing more choices to meet your specific requirements.\n\n* Make rwx_supported false by default: This feature removes the RWX dependency enabling Konveyor to work without RWX volume by default.\n\nThese minor improvements reflect our commitment to continuously refining and enhancing our platform to deliver an optimized and user-friendly experience. We value your feedback and encourage you to explore these enhancements as you leverage our latest release. You can install Konveyor 0.2.1 from [community operators](https://operatorhub.io/operator/konveyor-operator/konveyor-0.2/konveyor-operator.v0.2.1). If you encounter any issues or have suggestions for features, we encourage you to open an issue [here](https://github.com/konveyor/operator/issues/new).\n\nHappy Modernizing!\n"},"d5b87e59-70d9-5a8e-8d1e-ee0aff9d7dad":{"id":"d5b87e59-70d9-5a8e-8d1e-ee0aff9d7dad","title":"Tackle 2.1 release","slug":"/tackle-2-1-release/","description":"New features include a new report that gives details about the application data layer, easier CSV importing, bulk deletion of applications, and a more streamlined user experience.","tags":["Tackle"],"content":"---\nauthor: konveyor\ndate: 2022-09-14T07:00:00Z\ndescription: >-\n New features include a new report that gives details about the application data layer, easier CSV importing, bulk deletion of applications, and a more streamlined user experience.\nfeatured: true\nimage: tackle-2-1-release.png\ntags:\n - Tackle\ntitle: 'Tackle 2.1 release'\n---\n\nAfter the major milestone that [Tackle 2.0](/blog/tackle-2-new-capabilities/) represented, the community has continued gathering feedback from the field to further polish the feature set and provide value in the context of modernization, migration and adoption projects. This has led to Tackle 2.1, available now in [operatorhub.io](https://operatorhub.io/), a minor release that has been focused on stabilizing the project and providing a more streamlined user experience, while still delivering some new tooling. The new features include the following:\n\n- **Integration with the Tackle DiVA project:** New report available in the application analysis results providing detailed information about the application data layer, including an extensive inventory of transactions and accessed databases with detailed stack traces for each transaction.\n- **Automated creation of missing entities on CSV import:** Tags and Business Services are not required to exist in Tackle prior to the import anymore. This simplifies dealing with large CSV files and the import process overall.\n- **Bulk delete of applications:** Applications can now be deleted at bulk in the application inventory. This is especially useful when applications have been imported at bulk by mistake or with some errors.\n\nOnce again, I would like to congratulate all the different teams involved in the implementation, testing and documentation of this new release of Tackle. We continue building this project together in the community, so any feedback or feature request is definitely welcome. If you feel like something is missing or some feature is not behaving as expected, don’t hesitate to [open an issue in the Tackle main repository](https://github.com/konveyor/tackle2-hub/issues).\n\nHappy modernizing!\n"},"34b76663-da5d-5d41-80e7-163c298238cd":{"id":"34b76663-da5d-5d41-80e7-163c298238cd","title":"Tackle 2: New capabilities for modernizing applications to leverage Kubernetes","slug":"/tackle-2-new-capabilities/","description":"New management, assessment, and analysis capabilities will help you streamline the modernization of your application portfolio to Kubernetes. See what is new with the open source tool Tackle 2.0.","tags":["Tackle"],"content":"---\nauthor: rnissen\ndate: 2022-06-16T07:00:00Z\ndescription: >-\n New management, assessment, and analysis capabilities will help you streamline the modernization of your application portfolio to Kubernetes. See what is new with the open source tool Tackle 2.0.\nfeatured: true\nimage: tackle-2.png\ntags:\n - Tackle\ntitle: 'Tackle 2: New capabilities for modernizing applications to leverage Kubernetes'\n---\n\nBy Ramón Román Nissen\n\nWe’re thrilled to announce that Tackle 2.0 is now available in [operatorhub.io](https://operatorhub.io/). This new release marks a major milestone for the Tackle project, with a new architecture focused on enhancing performance, scalability and more importantly, extensibility of the tooling available in the Tackle toolkit.\n\nThis version includes the seamless integration with the analysis capabilities of the Windup project, enabling Tackle to effectively manage, assess and now also analyze applications to have a holistic view at your portfolio when dealing with large scale modernization and Kubernetes adoption initiatives. This is essential to provide key insights that allow Architects leading these massive projects to make informed decisions, thus reducing risks and making the required effort measurable and predictable.\n\nThe following is a list of the exciting new features included in Tackle 2.0:\n\n- **Administrator perspective**: Dedicated perspective to manage tool-wide configuration, with a similar approach and design to the OpenShift Administrator Perspective.\n- **Enhanced RBAC**: Three new differentiated personas with different permissions — Administrator, Architect and Migrator\n- **Integration with repositories**: Full integration with source code (Git, Subversion) and binaries (Maven) repositories to automate the retrieval of applications for analysis.\n- **Credentials management**: Secure store for multiple credential types (source control, Maven settings files, proxy). Credentials are managed by Administrators and assigned by Architects to applications.\n- **Proxy integration**: HTTP and HTTPS proxy configuration can be managed in the Tackle UI.\n- **Analysis module**: Full integration with the Windup project to allow the execution of application analysis from the application inventory.\n- **Enhanced analysis modes**: Aside from source and binary analysis modes, now Tackle includes the Source + Dependencies mode that parses the POM file available in the source repository to gather dependencies from corporate or public artifact repositories, adding them to the scope of the analysis.\n- **Analysis scope selection**: Simplified user experience to configure the analysis scope, with the possibility to force the analysis of known Open Source libraries.\n- **Authless deployment**: Tackle can now be optionally deployed without Keycloak, allowing full unauthenticated admin access to the tool. This is especially useful when deploying the tool in resource constrained environments like local instances of Minikube, where only a single user would have access to it.\n- **Seamless upgrades**: Tackle lifecycle is now managed by a new operator with Capability Level II, allowing seamless upgrades between GA versions.\n\nI would like to take the chance to congratulate the engineering teams involved in the development of this new release of Tackle for making this major leap forward possible. Of course, this has to be extended as well to the UI/UX, QE and Documentation teams that made sure our tool is usable and reliable.\n\nMake sure you visit [the new official documentation website](https://konveyor.github.io/tackle2/) for Tackle 2 to get started with the tool. We will keep updating the documentation to make sure we cover all the use cases and scenarios in which Tackle can be used. In case you find anything missing, please let us know by [creating an issue in the Konveyor documentation repository](https://github.com/konveyor/konveyor.github.io/issues).\n\nHappy modernizing!\n\n---\n\n_**Bio**: Ramón Román is the Product Manager for the Migration Toolkit for Applications within the Modernization and Migration Solutions team in Red Hat. Prior to that, he was part of Red Hat's Consulting organization, where he worked as an Architect in the field, helping customers succeed in large-scale application migrations and Red Hat OpenShift adoption 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GMT<![CDATA[Modernize Petclinic App to Kubernetes Using Konveyor]]>https://www.konveyor.io/modernize-petclinic-to-k8s-using-konveyor/https://www.konveyor.io/modernize-petclinic-to-k8s-using-konveyor/Tue, 11 Jul 2023 00:00:00 GMT<![CDATA[Konveyor v0.2.1 Release Announcement]]>https://www.konveyor.io/release-announcement-0-2-1/https://www.konveyor.io/release-announcement-0-2-1/Thu, 06 Jul 2023 00:00:00 GMT<![CDATA[Reflecting on Large-Scale Cloud-Native Modernizations at KubeCon 23]]><![CDATA[Konveyor Community Latest Blog Posts]]>https://www.konveyor.ioGatsbyJSThu, 21 Sep 2023 18:59:04 GMT<![CDATA[One Year in the CNCF Sandbox- Konveyor's Reflective Journey]]>https://www.konveyor.io/one-year-cncf-sandbox-konveyor-reflective-journey/https://www.konveyor.io/one-year-cncf-sandbox-konveyor-reflective-journey/Thu, 21 Sep 2023 00:00:00 GMT<![CDATA[Modernize Petclinic App to Kubernetes Using 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                          Konveyor is now a Cloud Native Computing Foundation (CNCF) Sandbox project

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                          Konveyor is now a Cloud Native Computing Foundation (CNCF) Sandbox project

                          Posts under AppModernization

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                          Konveyor is now a Cloud Native Computing Foundation (CNCF) Sandbox project

                          Tags

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                          Konveyor is now a Cloud Native Computing Foundation (CNCF) Sandbox project

                          Tags

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                          Konveyor is now a Cloud Native Computing Foundation (CNCF) Sandbox project

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                          Konveyor is now a Cloud Native Computing Foundation (CNCF) Sandbox project

                          Posts under Konveyor

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                          Konveyor is now a Cloud Native Computing Foundation (CNCF) Sandbox project

                          Posts under Kubernetes

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                          Konveyor is now a Cloud Native Computing Foundation (CNCF) Sandbox project

                          Posts under Kubernetes

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