CHANGELOG.md

Change Log

All notable changes to this project will be documented in this file.

The format is based on Keep a Changelog, and this project adheres to Semantic Versioning.

UNRELEASED

Added

Changed

• enforce ssl on pipeline bucket in sagemaker templates module

v1.7.2

Added

Changed

• update MWAA to 2.10.1
• update MWAA dependencies
• update ray modules to use kubectl handler role & update CDK to 2.166.0
• update IDF module versions to 1.13.0
• pin MWAA requirements file version

v1.7.1

Added

• added mlflow-ai-gw-image module

Changed

• changed ray-image to pull from AWS Public ECR to avoid docker pull rate limits
• changed ray-orchestrator to not retrieve full training job logs and avoid States.DataLimitExceeded
• update ray-on-eks manifest cluster resources

v1.7.0

Added

• added GitHub as code repository option along with AWS CodeCommit for sagemaker templates batch_inference, finetune_llm_evaluation, hf_import_models and xgboost_abalone
• added ray-orchestrator module
• added GitHub as alternate option for code repository support along with AWS CodeCommit for sagemaker-templates-service-catalog module
• added SageMaker ground truth labeling module

Changed

• updated manifests to idf release 1.12.0

v1.6.0

Added

• added new manifest manifests/fine-tuning-6B

Changed

• updated mlflow version to 2.16.0 to support LLM tracing
• remove CDK overhead from mlflow-image module
• renamed mlflow manifests and updated README.MD
• added head tolerations & node labels for flexible ray cluster pods scheduling

v1.5.0

Added

• added documentation for MWAA Sagemaker training DAG manifest
• added documentation for Ray on EKS manifests
• added network isolation and inter container encryption for xgboost template
• added partition support for modules:
  • fmops/sagemaker-jumpstart-fm-endpoint
  • sagemaker/sagemaker-endpoint
  • sagemaker/sagemaker-notebook
  • sagemaker/sagemaker-studio
• added Bedrock fine-tuning manifest

Changed

• added accelerate as extra for transformers in finetune llm template
• limited bucket name length in templates to avoid pipeline failures when using long project names
• increased timeout on finetune_llm_evaluation project from 1 hour (default) to 4 hours
• pin ray-operator, ray-cluster, and ray-image modules versions
• pin module versions for all manifests
• the sagemaker/sagemaker-model-package-promote-pipeline module no longer generates a Docker image
• lowercase fine-tuning-6b deployment name due to CDK resource naming constraints

v1.4.0

Added

• adds workflow specific to changes for requirements-dev.txt so all static checks are run
• add ray-cluster module based on kuberay-helm charts
• added FSx for Lustre to ray-on-eks manifest & persistent volume claim to ray-cluster module
• added worker tolerations to ray-cluster module

Changed

• add integration tests for sagemaker-studio
• bump ecr module version to 1.10.0 to consume auto-delete images feature
• add service account to kuberay
• updated get-modules workflow to only run tests against changed files in modules/**
• Updated the sagemaker-templates-service-catalog module documentation to match the code layout.
• Modernize sagemaker-templates-service-catalog packaging and remove unused dependencies.
• remove custom manifests via dataFiles from ray-on-eks
• refactor ray-on-eks to ray-cluster and ray-operator modules
• downscope ray-operator service account permissions
• add an example custom ray-image
• document available manifests in readme
• add permission for SM studio to describe apps when domain resource isolation is enabled
• updated ray-on-eks manifest to use latest EKS IDF release

v1.3.0

Added

• added ray-on-eks, and manifests/ray-on-eks manifests
• added a sagemaker-model-monitoring-module module with an example of data quality, model quality, model bias, and model explainability monitoring of a SageMaker Endpoint
• added an option to enable data capture in the sagemaker-endpoint-module
• added a personas example module to deploy various roles required for an AI/ML project
• added sagemaker-model-cicd module
• added sagemaker_domain_arn as optional input for multiple modules, tags resources created with domain ARN to support domain resource isolation
• added enable_network_isolation as optional input for sagemaker-endpoint module, defaults to true
• added enable_domain_resource_isolation as optional input for sagemaker-studio module, adds IAM policy to studio roles preventing the access of resources from outside the domain, defaults to true
• added StudioDomainArn as output from sagemaker-studio module
• added enable_network_isolation as parameter for model_deploy template

Changed

• remove explicit module manifest account/region mappings from fmops-qna-rag
• moved CI/CD infra to separate repository and added self mutation pipeline to provision infra for module sagemaker-templates-service-catalog
• changed ECR encryption to KMS_MANAGED
• changed encryption for each bucket to KMS_MANAGED
• refactor airflow-dags module to use Pydantic
• fix inputs for bedrock-finetuning module not working
• add retention-type argument for the bucket in the bedrock-finetuning module
• fix broken dependencies for examples/airflow-dags
• use add_dependency to avoid deprecation warnings from CDK
• various typo fixes
• various clean-ups to the SageMaker Service Catalog templates
• fix opensearch removal policy
• update MWAA to 2.9.2
• update mwaa constraints
• limit length of id in model name to prevent model name becoming too long
• add permission for get secret value in hf_import_models template
• add manifests/tags parameters to one-click-template
• add integration tests for mlflow-image

v1.2.0

Added

• added multi-acc sagemaker-mlops manifest example

Changed

• fixed model deploy cross-account permissions
• added bucket and model package group names as stack outputs in the sagemaker-templates module
• refactor inputs for the following modules to use Pydantic:
  • mlflow-fargate
  • mlflow-image
  • sagemaker-studio
  • sagemaker-endpoint
  • sagemaker-templates-service-catalog
  • sagemaker-custom-kernel
  • qna-rag
• add CDK nag to qna-rag module
• rename seedfarmer project name to aiops
• chore: adding some missing auto_delete attributes
• chore: Add auto_delete to mlflow-fargate elb access logs bucket
• updating storage/ecr module to latest pending v1.8.0 of IDF
• enabled ECR image scan on push

v1.1.0

Added

• added managed autoscaling config to sagemaker-endpoint module
• added SSO support in sagemaker-studio module
• added VPC/subnets/sg config for multi-account project template to sagemaker-templates-service-catalog module
• added sagemaker-custom-kernel module
• added batch inference project template to sagemaker-templates-service-catalog module
• added EFS removal policy to mlflow-fargate module
• added mwaa module with example dag which demonstrates the MLOps in Airflow
• added sagemaker-model-event-bus module.
• added sagemaker-model-package-group module.
• added sagemaker-model-package-promote-pipeline module.
• added sagemaker-hugging-face-endpoint module
• added hf_import_models template to import hugging face models
• added qna-rag module
• added bedrock-finetuning module

Changed

• reogranized manifests by use-case
• add account/region props for project templates in sagemaker-templates-service-catalog module
• fix sagemaker-templates-service-catalog model deploy role lookup issue & abalone_xgboost model registry permissions
• update sagemaker-custom-kernel module IAM permissions
• split xgboost_abalone and model_deploy project templates in sagemaker-templates-service-catalog module
• add support for other AWS partitions
• update MySQL instance to use T3 instance type
• upgrade cdk_ecr_deployment version to fix the deprecated go1.x lambda runtime

Removed

• remove AmazonSageMakerFullAccess from multi_account_basic template in the sagemaker-templates-service-catalog module
• remove AmazonSageMakerFullAccess from sagemaker-endpoint module

v1.0.0

Added

• added sagemaker-templates-service-catalog module with multi_account_basic project template
• bump cdk & ecr deployment version to fix deprecated custom resource runtimes issue in mlflow-image
• added sagemaker-jumpstart-fm-endpoint module
• added RDS persistence layer to MLFlow modules
• added mlflow-image and mlflow-fargate modules
• added sagemaker-studio module
• added sagemaker-endpoint module
• added sagemaker-notebook module

Changed

• refactor validation script to use ruff instead of black and isort

Removed