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diff --git a/docs/book/component-guide/README.md b/docs/book/component-guide/README.md
@@ -2,6 +2,11 @@
 description: Overview of categories of MLOps components and third-party integrations.
 ---
 
+{% hint style="warning" %}
+This is an older version of the ZenML documentation. To read and view the latest version please [visit this up-to-date URL](https://docs.zenml.io).
+{% endhint %}
+
+
 # 📜 Overview
 
 If you are new to the world of MLOps, it is often daunting to be immediately faced with a sea of tools that seemingly all promise and do the same things. It is useful in this case to try to categorize tools in various groups in order to understand their value in your toolchain in a more precise manner.

diff --git a/docs/book/component-guide/alerters/alerters.md b/docs/book/component-guide/alerters/alerters.md
@@ -2,6 +2,11 @@
 description: Sending automated alerts to chat services.
 ---
 
+{% hint style="warning" %}
+This is an older version of the ZenML documentation. To read and view the latest version please [visit this up-to-date URL](https://docs.zenml.io).
+{% endhint %}
+
+
 # Alerters
 
 **Alerters** allow you to send messages to chat services (like Slack, Discord, Mattermost, etc.) from within your

diff --git a/docs/book/component-guide/alerters/custom.md b/docs/book/component-guide/alerters/custom.md
@@ -2,6 +2,11 @@
 description: Learning how to develop a custom alerter.
 ---
 
+{% hint style="warning" %}
+This is an older version of the ZenML documentation. To read and view the latest version please [visit this up-to-date URL](https://docs.zenml.io).
+{% endhint %}
+
+
 # Develop a Custom Alerter
 
 {% hint style="info" %}

diff --git a/docs/book/component-guide/alerters/discord.md b/docs/book/component-guide/alerters/discord.md
@@ -2,6 +2,11 @@
 description: Sending automated alerts to a Discord channel.
 ---
 
+{% hint style="warning" %}
+This is an older version of the ZenML documentation. To read and view the latest version please [visit this up-to-date URL](https://docs.zenml.io).
+{% endhint %}
+
+
 # Discord Alerter
 
 The `DiscordAlerter` enables you to send messages to a dedicated Discord channel 

diff --git a/docs/book/component-guide/alerters/slack.md b/docs/book/component-guide/alerters/slack.md
@@ -2,6 +2,11 @@
 description: Sending automated alerts to a Slack channel.
 ---
 
+{% hint style="warning" %}
+This is an older version of the ZenML documentation. To read and view the latest version please [visit this up-to-date URL](https://docs.zenml.io).
+{% endhint %}
+
+
 # Slack Alerter
 
 The `SlackAlerter` enables you to send messages to a dedicated Slack channel directly from within your ZenML pipelines.

diff --git a/docs/book/component-guide/annotators/annotators.md b/docs/book/component-guide/annotators/annotators.md
@@ -2,6 +2,11 @@
 description: Annotating the data in your workflow.
 ---
 
+{% hint style="warning" %}
+This is an older version of the ZenML documentation. To read and view the latest version please [visit this up-to-date URL](https://docs.zenml.io).
+{% endhint %}
+
+
 # Annotators
 
 Annotators are a stack component that enables the use of data annotation as part of your ZenML stack and pipelines. You

diff --git a/docs/book/component-guide/annotators/argilla.md b/docs/book/component-guide/annotators/argilla.md
@@ -2,6 +2,11 @@
 description: Annotating data using Argilla.
 ---
 
+{% hint style="warning" %}
+This is an older version of the ZenML documentation. To read and view the latest version please [visit this up-to-date URL](https://docs.zenml.io).
+{% endhint %}
+
+
 # Argilla
 
 [Argilla](https://github.com/argilla-io/argilla) is an open-source data curation

diff --git a/docs/book/component-guide/annotators/custom.md b/docs/book/component-guide/annotators/custom.md
@@ -2,6 +2,11 @@
 description: Learning how to develop a custom annotator.
 ---
 
+{% hint style="warning" %}
+This is an older version of the ZenML documentation. To read and view the latest version please [visit this up-to-date URL](https://docs.zenml.io).
+{% endhint %}
+
+
 # Develop a Custom Annotator
 
 {% hint style="info" %}

diff --git a/docs/book/component-guide/annotators/label-studio.md b/docs/book/component-guide/annotators/label-studio.md
@@ -2,6 +2,11 @@
 description: Annotating data using Label Studio.
 ---
 
+{% hint style="warning" %}
+This is an older version of the ZenML documentation. To read and view the latest version please [visit this up-to-date URL](https://docs.zenml.io).
+{% endhint %}
+
+
 # Label Studio
 
 Label Studio is one of the leading open-source annotation platforms available to data scientists and ML practitioners.

diff --git a/docs/book/component-guide/annotators/pigeon.md b/docs/book/component-guide/annotators/pigeon.md
@@ -2,6 +2,11 @@
 description: Annotating data using Pigeon.
 ---
 
+{% hint style="warning" %}
+This is an older version of the ZenML documentation. To read and view the latest version please [visit this up-to-date URL](https://docs.zenml.io).
+{% endhint %}
+
+
 # Pigeon
 
 Pigeon is a lightweight, open-source annotation tool designed for quick and easy labeling of data directly within Jupyter notebooks. It provides a simple and intuitive interface for annotating various types of data, including:

diff --git a/docs/book/component-guide/annotators/prodigy.md b/docs/book/component-guide/annotators/prodigy.md
@@ -2,6 +2,11 @@
 description: Annotating data using Prodigy.
 ---
 
+{% hint style="warning" %}
+This is an older version of the ZenML documentation. To read and view the latest version please [visit this up-to-date URL](https://docs.zenml.io).
+{% endhint %}
+
+
 # Prodigy
 
 [Prodigy](https://prodi.gy/) is a modern annotation tool for creating training

diff --git a/docs/book/component-guide/artifact-stores/artifact-stores.md b/docs/book/component-guide/artifact-stores/artifact-stores.md
@@ -2,6 +2,11 @@
 description: Setting up a persistent storage for your artifacts.
 ---
 
+{% hint style="warning" %}
+This is an older version of the ZenML documentation. To read and view the latest version please [visit this up-to-date URL](https://docs.zenml.io).
+{% endhint %}
+
+
 # Artifact Stores
 
 The Artifact Store is a central component in any MLOps stack. As the name suggests, it acts as a data persistence layer where artifacts (e.g. datasets, models) ingested or generated by the machine learning pipelines are stored.

diff --git a/docs/book/component-guide/artifact-stores/azure.md b/docs/book/component-guide/artifact-stores/azure.md
@@ -2,6 +2,11 @@
 description: Storing artifacts using Azure Blob Storage
 ---
 
+{% hint style="warning" %}
+This is an older version of the ZenML documentation. To read and view the latest version please [visit this up-to-date URL](https://docs.zenml.io).
+{% endhint %}
+
+
 # Azure Blob Storage
 
 The Azure Artifact Store is an [Artifact Store](./artifact-stores.md) flavor provided with the Azure ZenML integration that uses [the Azure Blob Storage managed object storage service](https://azure.microsoft.com/en-us/services/storage/blobs/) to store ZenML artifacts in an Azure Blob Storage container.

diff --git a/docs/book/component-guide/artifact-stores/custom.md b/docs/book/component-guide/artifact-stores/custom.md
@@ -2,6 +2,11 @@
 description: Learning how to develop a custom artifact store.
 ---
 
+{% hint style="warning" %}
+This is an older version of the ZenML documentation. To read and view the latest version please [visit this up-to-date URL](https://docs.zenml.io).
+{% endhint %}
+
+
 # Develop a custom artifact store
 
 {% hint style="info" %}

diff --git a/docs/book/component-guide/artifact-stores/gcp.md b/docs/book/component-guide/artifact-stores/gcp.md
@@ -2,6 +2,11 @@
 description: Storing artifacts using GCP Cloud Storage.
 ---
 
+{% hint style="warning" %}
+This is an older version of the ZenML documentation. To read and view the latest version please [visit this up-to-date URL](https://docs.zenml.io).
+{% endhint %}
+
+
 # Google Cloud Storage (GCS)
 
 The GCS Artifact Store is an [Artifact Store](./artifact-stores.md) flavor provided with the GCP ZenML integration that uses [the Google Cloud Storage managed object storage service](https://cloud.google.com/storage/docs/introduction) to store ZenML artifacts in a GCP Cloud Storage bucket.

diff --git a/docs/book/component-guide/artifact-stores/local.md b/docs/book/component-guide/artifact-stores/local.md
@@ -2,6 +2,11 @@
 description: Storing artifacts on your local filesystem.
 ---
 
+{% hint style="warning" %}
+This is an older version of the ZenML documentation. To read and view the latest version please [visit this up-to-date URL](https://docs.zenml.io).
+{% endhint %}
+
+
 # Local Artifact Store
 
 The local Artifact Store is a built-in ZenML [Artifact Store](./artifact-stores.md) flavor that uses a folder on your local filesystem to store artifacts.

diff --git a/docs/book/component-guide/artifact-stores/s3.md b/docs/book/component-guide/artifact-stores/s3.md
@@ -2,6 +2,11 @@
 description: Storing artifacts in an AWS S3 bucket.
 ---
 
+{% hint style="warning" %}
+This is an older version of the ZenML documentation. To read and view the latest version please [visit this up-to-date URL](https://docs.zenml.io).
+{% endhint %}
+
+
 # Amazon Simple Cloud Storage (S3)
 
 The S3 Artifact Store is an [Artifact Store](./artifact-stores.md) flavor provided with the S3 ZenML integration that uses [the AWS S3 managed object storage service](https://aws.amazon.com/s3/) or one of the self-hosted S3 alternatives, such as [MinIO](https://min.io/) or [Ceph RGW](https://ceph.io/en/discover/technology/#object), to store artifacts in an S3 compatible object storage backend.

diff --git a/docs/book/component-guide/component-guide.md b/docs/book/component-guide/component-guide.md
@@ -2,6 +2,11 @@
 description: Overview of categories of MLOps components.
 ---
 
+{% hint style="warning" %}
+This is an older version of the ZenML documentation. To read and view the latest version please [visit this up-to-date URL](https://docs.zenml.io).
+{% endhint %}
+
+
 # 📜 Overview
 
 If you are new to the world of MLOps, it is often daunting to be immediately faced with a sea of tools that seemingly all promise and do the same things. It is useful in this case to try to categorize tools in various groups in order to understand their value in your toolchain in a more precise manner.

diff --git a/docs/book/component-guide/container-registries/aws.md b/docs/book/component-guide/container-registries/aws.md
@@ -2,6 +2,11 @@
 description: Storing container images in Amazon ECR.
 ---
 
+{% hint style="warning" %}
+This is an older version of the ZenML documentation. To read and view the latest version please [visit this up-to-date URL](https://docs.zenml.io).
+{% endhint %}
+
+
 # Amazon Elastic Container Registry (ECR)
 
 The AWS container registry is a [container registry](./container-registries.md) flavor provided with the ZenML `aws` integration and uses [Amazon ECR](https://aws.amazon.com/ecr/) to store container images.

diff --git a/docs/book/component-guide/container-registries/azure.md b/docs/book/component-guide/container-registries/azure.md
@@ -2,6 +2,11 @@
 description: Storing container images in Azure.
 ---
 
+{% hint style="warning" %}
+This is an older version of the ZenML documentation. To read and view the latest version please [visit this up-to-date URL](https://docs.zenml.io).
+{% endhint %}
+
+
 # Azure Container Registry
 
 The Azure container registry is a [container registry](./container-registries.md) flavor that comes built-in with ZenML and uses the [Azure Container Registry](https://azure.microsoft.com/en-us/services/container-registry/) to store container images.

diff --git a/docs/book/component-guide/container-registries/container-registries.md b/docs/book/component-guide/container-registries/container-registries.md
@@ -2,6 +2,11 @@
 description: Setting up a storage for Docker images.
 ---
 
+{% hint style="warning" %}
+This is an older version of the ZenML documentation. To read and view the latest version please [visit this up-to-date URL](https://docs.zenml.io).
+{% endhint %}
+
+
 # Container Registries
 
 The container registry is an essential part of most remote MLOps stacks. It is used to store container images that are

diff --git a/docs/book/component-guide/container-registries/custom.md b/docs/book/component-guide/container-registries/custom.md
@@ -2,6 +2,11 @@
 description: Learning how to develop a custom container registry.
 ---
 
+{% hint style="warning" %}
+This is an older version of the ZenML documentation. To read and view the latest version please [visit this up-to-date URL](https://docs.zenml.io).
+{% endhint %}
+
+
 # Develop a custom container registry
 
 {% hint style="info" %}

diff --git a/docs/book/component-guide/container-registries/default.md b/docs/book/component-guide/container-registries/default.md
@@ -2,6 +2,11 @@
 description: Storing container images locally.
 ---
 
+{% hint style="warning" %}
+This is an older version of the ZenML documentation. To read and view the latest version please [visit this up-to-date URL](https://docs.zenml.io).
+{% endhint %}
+
+
 # Default Container Registry
 
 The Default container registry is a [container registry](./container-registries.md) flavor that comes built-in with ZenML and allows container registry URIs of any format.

diff --git a/docs/book/component-guide/container-registries/dockerhub.md b/docs/book/component-guide/container-registries/dockerhub.md
@@ -2,6 +2,11 @@
 description: Storing container images in DockerHub.
 ---
 
+{% hint style="warning" %}
+This is an older version of the ZenML documentation. To read and view the latest version please [visit this up-to-date URL](https://docs.zenml.io).
+{% endhint %}
+
+
 # DockerHub
 
 The DockerHub container registry is a [container registry](./container-registries.md) flavor that comes built-in with ZenML and uses [DockerHub](https://hub.docker.com/) to store container images.

diff --git a/docs/book/component-guide/container-registries/gcp.md b/docs/book/component-guide/container-registries/gcp.md
@@ -2,6 +2,11 @@
 description: Storing container images in GCP.
 ---
 
+{% hint style="warning" %}
+This is an older version of the ZenML documentation. To read and view the latest version please [visit this up-to-date URL](https://docs.zenml.io).
+{% endhint %}
+
+
 # Google Cloud Container Registry
 
 The GCP container registry is a [container registry](./container-registries.md) flavor that comes built-in with ZenML and uses the [Google Artifact Registry](https://cloud.google.com/artifact-registry).

diff --git a/docs/book/component-guide/container-registries/github.md b/docs/book/component-guide/container-registries/github.md
@@ -2,6 +2,11 @@
 description: Storing container images in GitHub.
 ---
 
+{% hint style="warning" %}
+This is an older version of the ZenML documentation. To read and view the latest version please [visit this up-to-date URL](https://docs.zenml.io).
+{% endhint %}
+
+
 # GitHub Container Registry
 
 The GitHub container registry is a [container registry](./container-registries.md) flavor that comes built-in with ZenML and uses the [GitHub Container Registry](https://docs.github.com/en/packages/working-with-a-github-packages-registry/working-with-the-container-registry) to store container images.

diff --git a/docs/book/component-guide/data-validators/custom.md b/docs/book/component-guide/data-validators/custom.md
@@ -2,6 +2,11 @@
 description: How to develop a custom data validator
 ---
 
+{% hint style="warning" %}
+This is an older version of the ZenML documentation. To read and view the latest version please [visit this up-to-date URL](https://docs.zenml.io).
+{% endhint %}
+
+
 # Develop a custom data validator
 
 {% hint style="info" %}

diff --git a/docs/book/component-guide/data-validators/data-validators.md b/docs/book/component-guide/data-validators/data-validators.md
@@ -4,6 +4,11 @@ description: >-
   your models with data profiling and validation
 ---
 
+{% hint style="warning" %}
+This is an older version of the ZenML documentation. To read and view the latest version please [visit this up-to-date URL](https://docs.zenml.io).
+{% endhint %}
+
+
 # Data Validators
 
 Without good data, even the best machine learning models will yield questionable results. A lot of effort goes into ensuring and maintaining data quality not only in the initial stages of model development, but throughout the entire machine learning project lifecycle. Data Validators are a category of ML libraries, tools and frameworks that grant a wide range of features and best practices that should be employed in the ML pipelines to keep data quality in check and to monitor model performance to keep it from degrading over time.

diff --git a/docs/book/component-guide/data-validators/deepchecks.md b/docs/book/component-guide/data-validators/deepchecks.md
@@ -4,6 +4,11 @@ description: >-
   suites
 ---
 
+{% hint style="warning" %}
+This is an older version of the ZenML documentation. To read and view the latest version please [visit this up-to-date URL](https://docs.zenml.io).
+{% endhint %}
+
+
 # Deepchecks
 
 The Deepchecks [Data Validator](./data-validators.md) flavor provided with the ZenML integration uses [Deepchecks](https://deepchecks.com/) to run data integrity, data drift, model drift and model performance tests on the datasets and models circulated in your ZenML pipelines. The test results can be used to implement automated corrective actions in your pipelines or to render interactive representations for further visual interpretation, evaluation and documentation.

diff --git a/docs/book/component-guide/data-validators/evidently.md b/docs/book/component-guide/data-validators/evidently.md
@@ -4,6 +4,11 @@ description: >-
   with Evidently profiling
 ---
 
+{% hint style="warning" %}
+This is an older version of the ZenML documentation. To read and view the latest version please [visit this up-to-date URL](https://docs.zenml.io).
+{% endhint %}
+
+
 # Evidently
 
 The Evidently [Data Validator](./data-validators.md) flavor provided with the ZenML integration uses [Evidently](https://evidentlyai.com/) to perform data quality, data drift, model drift and model performance analyses, to generate reports and run checks. The reports and check results can be used to implement automated corrective actions in your pipelines or to render interactive representations for further visual interpretation, evaluation and documentation.

diff --git a/docs/book/component-guide/data-validators/great-expectations.md b/docs/book/component-guide/data-validators/great-expectations.md
@@ -4,6 +4,11 @@ description: >-
   document the results
 ---
 
+{% hint style="warning" %}
+This is an older version of the ZenML documentation. To read and view the latest version please [visit this up-to-date URL](https://docs.zenml.io).
+{% endhint %}
+
+
 # Great Expectations
 
 The Great Expectations [Data Validator](./data-validators.md) flavor provided with the ZenML integration uses [Great Expectations](https://greatexpectations.io/) to run data profiling and data quality tests on the data circulated through your pipelines. The test results can be used to implement automated corrective actions in your pipelines. They are also automatically rendered into documentation for further visual interpretation and evaluation.

diff --git a/docs/book/component-guide/data-validators/whylogs.md b/docs/book/component-guide/data-validators/whylogs.md
@@ -4,6 +4,11 @@ description: >-
   data with whylogs/WhyLabs profiling.
 ---
 
+{% hint style="warning" %}
+This is an older version of the ZenML documentation. To read and view the latest version please [visit this up-to-date URL](https://docs.zenml.io).
+{% endhint %}
+
+
 # Whylogs
 
 The whylogs/WhyLabs [Data Validator](./data-validators.md) flavor provided with the ZenML integration uses [whylogs](https://whylabs.ai/whylogs) and [WhyLabs](https://whylabs.ai) to generate and track data profiles, highly accurate descriptive representations of your data. The profiles can be used to implement automated corrective actions in your pipelines, or to render interactive representations for further visual interpretation, evaluation and documentation.

diff --git a/docs/book/component-guide/experiment-trackers/comet.md b/docs/book/component-guide/experiment-trackers/comet.md
@@ -2,6 +2,11 @@
 description: Logging and visualizing experiments with Comet.
 ---
 
+{% hint style="warning" %}
+This is an older version of the ZenML documentation. To read and view the latest version please [visit this up-to-date URL](https://docs.zenml.io).
+{% endhint %}
+
+
 # Comet
 
 The Comet Experiment Tracker is an [Experiment Tracker](./experiment-trackers.md) flavor provided with the Comet ZenML integration that uses [the Comet experiment tracking platform](https://www.comet.com/site/products/ml-experiment-tracking/) to log and visualize information from your pipeline steps (e.g., models, parameters, metrics).