AWS solutions documentation change
Summary
Simplified the revisions documentation by removing detailed version history and replacing it with a reference to the CHANGELOG.md file in the GitHub repository
Security assessment
The change is purely a documentation restructuring that removes detailed version history in favor of pointing to the changelog file. There is no evidence of security-related content being added or removed.
Diff
diff --git a/solutions/latest/mlops-workload-orchestrator/revisions.md index 1cbfaf00b..826202358 100644 --- a/solutions/latest/mlops-workload-orchestrator/revisions.md +++ b/solutions/latest/mlops-workload-orchestrator/revisions.md @@ -7,20 +7,3 @@ -Date | Change ----|--- -November 2020 | Initial release -January 2021 | Release v1.1.0: Model monitor pipeline to monitor the quality of deployed machine learning models. For more information about the changes, refer to the [CHANGELOG.md](https://github.com/aws-solutions/mlops-workload-orchestrator/blob/main/CHANGELOG.md) file in the GitHub repository. -March 2021 | Release v1.1.1: Updated the Amazon ECR scan on push property and repository names. For more information about the changes, refer to the [CHANGELOG.md](https://github.com/aws-solutions/mlops-workload-orchestrator/blob/main/CHANGELOG.md) file in the GitHub repository. -May 2021 | Release v.1.2.0: Added an option for multi-account deployments, and added the Custom Algorithm Image Builder pipeline. For more information about the changes, refer to the [CHANGELOG.md](https://github.com/aws-solutions/mlops-workload-orchestrator/blob/main/CHANGELOG.md) file in the GitHub repository. -June 2021 | Release v.1.3.0: Added the option to use Amazon SageMaker AI model registry, and the option to use AWS Organizations delegated administrator account (default option) to orchestrate the deployment of Machine Learning (ML) workloads across the AWS Organizations accounts. For more information about the changes, refer to the [CHANGELOG.md](https://github.com/aws-solutions/mlops-workload-orchestrator/blob/main/CHANGELOG.md) file in the GitHub repository. -September 2021 | Release v1.4.0: Added Amazon SageMaker AI model quality monitor pipeline to monitor the performance of a deployed model by comparing the predictions that the model makes with the actual ground truth labels that the model attempts to predict. For more information about the changes, refer to the [CHANGELOG.md](https://github.com/aws-solutions/mlops-workload-orchestrator/blob/main/CHANGELOG.md) file in the GitHub repository. -December 2021 | Release v1.4.1: Added documentation about how customers can integrate custom blueprints into the solution. Added a configurable flag to start/stop server-side error propagation. Updated APIs responses. For more information about the changes, refer to the [CHANGELOG.md](https://github.com/aws-solutions/mlops-workload-orchestrator/blob/main/CHANGELOG.md) file in the GitHub repository. -January 2022 | Release v1.5.0: The solution name was changed from “AWS MLOps Framework” to “MLOps Workload Orchestrator”. Added Amazon SageMaker AI model bias monitor pipeline to monitor predictions for bias on a regular basis, and generate alerts if bias beyond a certain threshold is detected. Added Amazon SageMaker AI explainability monitor to monitor predictions for feature attribution drift on a regular basis. For more information about the changes, refer to the [CHANGELOG.md](https://github.com/aws-solutions/mlops-workload-orchestrator/blob/main/CHANGELOG.md) file in the GitHub repository. -May 2022 | Release v2.0.0: Added three training pipelines to train ML models using Amazon SageMaker AI built-in algorithms and training job, hyperparameter tuning job, and autopilot job. Added Amazon EventBridge rules to monitor the state change of the training jobs. For more information about the changes, refer to the [CHANGELOG.md](https://github.com/aws-solutions/mlops-workload-orchestrator/blob/main/CHANGELOG.md) file in the GitHub repository. -August 2022 | Release v2.0.1: Updated IAM Role permissions with the new naming convention for temporary Amazon SageMaker AI endpoints used by the Amazon SageMaker AI Clarify Model Bias Monitor and Amazon SageMaker AI Clarify Model Explainability Monitor pipelines. Fixed breaking changes in protobuf library in versions greater than 3.20.1. Fixed empty image URL for the model training pipelines when using Amazon SageMaker AI Model Registry option. For more information about the changes, refer to the [CHANGELOG.md](https://github.com/aws-solutions/mlops-workload-orchestrator/blob/main/CHANGELOG.md) file in the GitHub repository. -November 2022 | Release v2.1.0: Added integration with Amazon SageMaker AI Model Card and Amazon SageMaker AI Model Dashboard features to allow customers to perform model card operations. All Amazon SageMaker AI resources (models, endpoints, training jobs, and model monitors) created by the solution will show up on the SageMaker AI Model Dashboard. Fixed missing IAM Role permissions used by the Amazon SageMaker AI Clarify Model Bias Monitor and Amazon SageMaker AI Clarify Model Explainability Monitor scheduling jobs. For more information about the changes, refer to the [CHANGELOG.md](https://github.com/aws-solutions/mlops-workload-orchestrator/blob/main/CHANGELOG.md) file in the GitHub repository. -January 2023 | Release v2.1.1: Updated Python libraries. Upgraded Python runtime to 3.10. For more information about the changes, refer to the [CHANGELOG.md](https://github.com/aws-solutions/mlops-workload-orchestrator/blob/main/CHANGELOG.md) file in the GitHub repository. -April 2023 | Release v2.1.2: Mitigated impact caused by new default settings for S3 Object Ownership (ACLs disabled) for all new S3 buckets. For more information about the changes, refer to the [CHANGELOG.md](https://github.com/aws-solutions/mlops-workload-orchestrator/blob/main/CHANGELOG.md) file in the GitHub repository. -August 2023 | Release v2.2.0: This release includes integration of this solution with AppRegistry and AWS Systems Manager Application Manager, migrating to AWS CDK v2, and upgrading to Python runtime 3.10. For more information about the changes, refer to the [CHANGELOG.md](https://github.com/aws-solutions/mlops-workload-orchestrator/blob/main/CHANGELOG.md) file in the GitHub repository. -November 2023 | Documentation update: Added [Confirm cost tags associated with the solution](./confirm-cost-tags-associated-with-the-solution.html) to the Monitoring the solution with AWS Service Catalog AppRegistry section. -May 2024 | Release v2.2.1: Updated package versions for Boto3, Botocore, and SageMaker to address CVE-2024-34072, CVE-2024-34073, updated requests due to CVE-2024-35195, increased Lambda memory sizes, `PutBucketTagging` permission added to Orchestrator Lambda IAM policy. For more information about the changes, refer to the [CHANGELOG.md](https://github.com/aws-solutions/mlops-workload-orchestrator/blob/main/CHANGELOG.md) file in the GitHub repository. -June 2024 | Release v2.2.2: Fixed upgrade issue with Lambda Custom Resource SageMaker AI layer copy to new blueprints bucket, requests updated to 2.32.3. For more information about the changes, refer to the [CHANGELOG.md](https://github.com/aws-solutions/mlops-workload-orchestrator/blob/main/CHANGELOG.md) file in the GitHub repository. -December 2024 | Release v2.2.3: Fixed issue with anonymized operation metrics collection, migrated the source for pipeline configuration file from CodeCommit to an S3 bucket, and patched security vulnerabilities. For more information about the changes, refer to the [CHANGELOG.md](https://github.com/aws-solutions/mlops-workload-orchestrator/blob/main/CHANGELOG.md) file in the GitHub repository. +Publication date: _November 2020_. + +Check the [CHANGELOG.md](https://github.com/aws-solutions/mlops-workload-orchestrator/blob/main/CHANGELOG.md) file in the GitHub repository to see all notable changes and updates to the software. The changelog provides a clear record of improvements and fixes for each version.