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AWS provide Well-Architecture Framework to build a secure, high-performance, resilient and efficient infrastructure for a wide variety of applications and workloads. AWS Well-Architected provides a consistent approach to helping customers and partners evaluate architectures and implement scalable designs.

The framework is based on six pillars:

  • Operational Excellence
  • Security
  • Reliability
  • Performance Efficiency
  • Cost Optimization
  • Sustainability

Operational Excellence

Operational excellence is defined as a commitment to build software correctly while consistently delivering a great customer experience. It contains best practices for organizing team, designing worload, operating it at scale, and evolving it over time.

The goal of operational excellence is to get new features and bug fixes into customer's hands quickly and reliably. Along the way, operational excellence drives towards continuous integration and continous delivery(CI/CD) by helping developers achieve high quality results consistently.

The following are the design principles for operational excellence in the cloud:

  • Perform operations as code: In the cloud, you can apply the same engineering discipline that you use for application code to your entire environment. You can define your entire workload (applications, infrastructure, etc.) as code and update it with code. You can script your operations procedures and automate their process by launching them in response to events. By performing operations as code, you limit human error and create consistent responses to events.

  • Make frequent, small, reversible changes: Design workloads to allow components to be updated regularly to increase the flow of beneficial changes into your workload. Make changes in small increments that can be reversed if they fail to aid in the identification and resolution of issues introduced to your environment (without affecting customers when possible).

  • Refine operations procedures frequently: As you use operations procedures, look for opportunities to improve them. As you evolve your workload, evolve your procedures appropriately. Set up regular game days to review and validate that all procedures are effective and that teams are familiar with them.

  • Anticipate failure: Perform “pre-mortem” exercises to identify potential sources of failure so that they can be removed or mitigated. Test your failure scenarios and validate your understanding of their impact. Test your response procedures to ensure they are effective and that teams are familiar with their process. Set up regular game days to test workload and team responses to simulated events.

  • Learn from all operational failures: Drive improvement through lessons learned from all operational events and failures. Share what is learned across teams and through the entire organization.

Security

The Security pillar encompasses the ability to protect data, systems, and assets to take advantage of cloud technologies to improve your security.

Before you architect any workload, you need to put in place practices that influence security. You will want to control who can do what. In addition, you want to be able to identify security incidents, protect your systems and services, and maintain the confidentiality and integrity of data through data protection. You should have a well-defined and practiced process for responding to security incidents. These tools and techniques are important because they support objectives such as preventing financial loss or complying with regulatory obligations.

The AWS Shared Responsibility Model helps organizations that adopt the cloud to achieve their security and compliance goals. Because AWS physically secures the infrastructure that supports our cloud services, as an AWS customer can focus on using services to accomplish your goals. The AWS Cloud also provides greater access to security data and an automated approach to responding to security events.

The following are the design principles for security in the cloud:

  • Implement a strong identity foundation: Implement the principle of least privilege and enforce separation of duties with appropriate authorization for each interaction with your AWS resources. Centralize identity management, and aim to eliminate reliance on long-term static credentials.

  • Maintain traceability: Monitor, alert, and audit actions and changes to your environment in real time. Integrate log and metric collection with systems to automatically investigate and take action.

  • Apply security at all layers: Apply a defense in depth approach with multiple security controls. Apply to all layers (for example, edge of network, VPC, load balancing, every instance and compute service, operating system, application, and code).

  • Automate security best practices: Automated software-based security mechanisms improve your ability to securely scale more rapidly and cost-effectively. Create secure architectures, including the implementation of controls that are defined and managed as code in version-controlled templates.

  • Protect data in transit and at rest: Classify your data into sensitivity levels and use mechanisms, such as encryption, tokenization, and access control where appropriate.

  • Keep people away from data: Use mechanisms and tools to reduce or eliminate the need for direct access or manual processing of data. This reduces the risk of mishandling or modification and human error when handling sensitive data.

  • Prepare for security events: Prepare for an incident by having incident management and investigation policy and processes that align to your organizational requirements. Run incident response simulations and use tools with automation to increase your speed for detection, investigation, and recovery.

Reliability

The Reliability pillar encompasses the ability of a workload to perform its intended function correctly and consistently when it’s expected to. This includes the ability to operate and test the workload through its total lifecycle. This paper provides in-depth, best practice guidance for implementing reliable workloads on AWS.

To achieve reliability, you must start with the foundations — an environment where Service Quotas and network topology accommodate the workload. The workload architecture of the distributed system must be designed to prevent and mitigate failures. The workload must handle changes in demand or requirements, and it must be designed to detect failure and automatically heal itself.

There are five design principles for reliability in the cloud:

  • Automatically recover from failure: By monitoring a workload for key performance indicators (KPIs), you can start automation when a threshold is breached. These KPIs should be a measure of business value, not of the technical aspects of the operation of the service. This provides for automatic notification and tracking of failures, and for automated recovery processes that work around or repair the failure. With more sophisticated automation, it’s possible to anticipate and remediate failures before they occur.

  • Test recovery procedures: In an on-premises environment, testing is often conducted to prove that the workload works in a particular scenario. Testing is not typically used to validate recovery strategies. In the cloud, you can test how your workload fails, and you can validate your recovery procedures. You can use automation to simulate different failures or to recreate scenarios that led to failures before. This approach exposes failure pathways that you can test and fix before a real failure scenario occurs, thus reducing risk.

  • Scale horizontally to increase aggregate workload availability: Replace one large resource with multiple small resources to reduce the impact of a single failure on the overall workload. Distribute requests across multiple, smaller resources to verify that they don’t share a common point of failure.

  • Stop guessing capacity: A common cause of failure in on-premises workloads is resource saturation, when the demands placed on a workload exceed the capacity of that workload (this is often the objective of denial of service attacks). In the cloud, you can monitor demand and workload utilization, and automate the addition or removal of resources to maintain the more efficient level to satisfy demand without over- or under-provisioning. There are still limits, but some quotas can be controlled and others can be managed (see Manage Service Quotas and Constraints).

  • Manage change in automation: Changes to your infrastructure should be made using automation. The changes that must be managed include changes to the automation, which then can be tracked and reviewed.

Performance efficiency

The Performance Efficiency pillar includes the ability to use computing resources efficiently to meet system requirements, and to maintain that efficiency as demand changes and technologies evolve.

Take a data-driven approach to building a high-performance architecture. Gather data on all aspects of the architecture, from the high-level design to the selection and configuration of resource types.

Reviewing your choices on a regular basis validates that you are taking advantage of the continually evolving AWS Cloud. Monitoring verifies that you are aware of any deviance from expected performance. Make trade-offs in your architecture to improve performance, such as using compression or caching, or relaxing consistency requirements.

  • Democratize advanced technologies: Make advanced technology implementation smoother for your team by delegating complex tasks to your cloud vendor. Rather than asking your IT team to learn about hosting and running a new technology, consider consuming the technology as a service. For example, NoSQL databases, media transcoding, and machine learning are all technologies that require specialized expertise. In the cloud, these technologies become services that your team can consume, permitting your team to focus on product development rather than resource provisioning and management.

  • Go global in minutes: Deploying your workload in multiple AWS Regions around the world permits you to provide lower latency and a better experience for your customers at minimal cost.

  • Use serverless architectures: Serverless architectures remove the need for you to run and maintain physical servers for traditional compute activities. For example, serverless storage services can act as static websites (removing the need for web servers) and event services can host code. This removes the operational burden of managing physical servers, and can lower transactional costs because managed services operate at cloud scale.

  • Experiment more often: With virtual and automatable resources, you can quickly carry out comparative testing using different types of instances, storage, or configurations.

  • Consider mechanical sympathy: Understand how cloud services are consumed and always use the technology approach that aligns with your workload goals. For example, consider data access patterns when you select database or storage approaches.

Cost Optimization

The Cost Optimization pillar includes the ability to run systems to deliver business value at the lowest price point.

As with the other pillars within the Well-Architected Framework, there are tradeoffs to consider, for example, whether to optimize for speed-to=market or for cost. In some cases, it's more efficient to optimize for speed, going to market quickly, shipping new features, or meeting a deadlin, rather than investing in upfront cost optimization. Design decisions are sometimes directed by haste rather than spend time benchmarking for the most cost-optimal deplyments. However, this is a reasonable choice when you must "lift and shift" resources from your on-premises environment to ther cloud and then optimize afterwards. Investing the right amount of effort in a cost optimization strategy up front permits you to realize the economix benefits of the cloud more readily by achieving a conststent adherence to best practices and avoiding unnecessary over prosioning.

There are five design principles for cost optimization in the cloud:

  • Implement Cloud Financial Management: To achieve financial success and accelerate business value realization in the cloud, invest in Cloud Financial Management and Cost Optimization. Your organization should dedicate time and resources to build capability in this new domain of technology and usage management. Similar to your Security or Operational Excellence capability, you need to build capability through knowledge building, programs, resources, and processes to become a cost-efficient organization.

  • Adopt a consumption model: Pay only for the computing resources that you require and increase or decrease usage depending on business requirements, not by using elaborate forecasting. For example, development and test environments are typically only used for eight hours a day during the work week. You can stop these resources when they are not in use for a potential cost savings of 75% (40 hours versus 168 hours).

  • Measure overall efficiency: Measure the business output of the workload and the costs associated with delivering it. Use this measure to know the gains you make from increasing output and reducing costs.

  • Stop spending money on undifferentiated heavy lifting: AWS does the heavy lifting of data center operations like racking, stacking, and powering servers. It also removes the operational burden of managing operating systems and applications with managed services. This permits you to focus on your customers and business projects rather than on IT infrastructure.

  • Analyze and attribute expenditure: The cloud makes it simple to accurately identify the usage and cost of systems, which then permits transparent attribution of IT costs to individual workload owners. This helps measure return on investment (ROI) and gives workload owners an opportunity to optimize their resources and reduce costs.