- Add LakeFormationConfig class to configure Lake Formation governance on offline stores
- Implement FeatureGroup subclass with Lake Formation integration capabilities
- Add helper methods for S3 URI/ARN conversion and Lake Formation role management
- Add S3 deny policy generation for Lake Formation access control
- Implement Lake Formation resource registration and S3 bucket policy setup
- Add integration tests for Lake Formation feature store workflows
- Add unit tests for Lake Formation configuration and policy generation
- Update feature_store module exports to include FeatureGroup and LakeFormationConfig
- Update API documentation to include Feature Store section in sagemaker_mlops.rst
- Enable fine-grained access control for feature store offline stores using AWS Lake Formation

Replace 10 bare print() calls with a single logger.info() call for the
S3 deny policy output in enable_lake_formation(). This makes the policy
display consistent with the rest of the LF workflow which uses logger.

Update 12 tests to mock the logger instead of builtins.print.

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X-AI-Prompt: replace print with logger.info for s3 bucket policy display in enable_lake_formation
X-AI-Tool: kiro-cli

Rename the mlops FeatureGroup class to FeatureGroupManager to
distinguish it from the core FeatureGroup base class. Update all
references in unit and integration lake formation tests. Fix missing
comma in __init__.py __all__ list.
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X-AI-Prompt: rename FeatureGroup to FeatureGroupManager and update lakeformation tests
X-AI-Tool: kiro-cli

…ate, update, get functions