Revisions
| 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 |
| 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 |
| 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 |
| June 2021 |
Release v.1.3.0: Added the option to use Amazon SageMaker
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 |
| September 2021 |
Release v1.4.0: Added Amazon SageMaker 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 |
| 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 |
| January 2022 |
Release v1.5.0: The solution name was changed from “AWS MLOps Framework” to “MLOps Workload Orchestrator”. Added
Amazon SageMaker 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 explainability monitor to monitor predictions for
feature attribution drift on a regular basis. For more
information about the changes, refer to the
CHANGELOG.md |
| May 2022 |
Release v2.0.0: Added three training pipelines to train ML
models using Amazon SageMaker 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 |
| August 2022 | Release v2.0.1: Updated IAM Role permissions with the new naming convention for
temporary Amazon SageMaker endpoints used by the Amazon SageMaker Clarify Model Bias Monitor and
Amazon SageMaker 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 Model Registry option. For more information about
the changes, refer to the CHANGELOG.md |
| November 2022 | Release v2.1.0: Added integration with Amazon SageMaker Model Card and Amazon SageMaker Model
Dashboard features to allow customers to perform model card operations. All Amazon SageMaker
resources (models, endpoints, training jobs, and model monitors) created by the solution
will show up on the SageMaker Model Dashboard. Fixed missing IAM Role permissions used by
the Amazon SageMaker Clarify Model Bias Monitor and Amazon SageMaker Clarify Model Explainability
Monitor scheduling jobs. For more information about the changes, refer to the CHANGELOG.md |
| 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 |
| 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 |
| 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 |
| November 2023 | Documentation update: Added Confirm cost tags associated with the solution 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, |
| June 2024 |
Release v2.2.2: Fixed upgrade issue with Lambda Custom Resource SageMaker layer copy to
new blueprints bucket, requests updated to 2.32.3. For more information about the
changes, refer to the CHANGELOG.md |
