A company needs an AWS solution that will automatically create versions of ML models as the models are created. Which solution will meet this requirement?

Question

Options

• AAmazon Elastic Container Registry (Amazon ECR)
• BModel packages from Amazon SageMaker Marketplace
• CAmazon SageMaker ML Lineage Tracking
• DAmazon SageMaker Model Registry

• A
  6% (2)
• B
  3% (1)
• D
  91% (31)

Explanation

Amazon SageMaker Model Registry is designed specifically to catalog, version, and manage ML models throughout their lifecycle - it automatically tracks model versions as they are created, supports approval workflows, and integrates with SageMaker Pipelines for CI/CD of ML models.

Why the distractors are wrong:

• A (Amazon ECR) stores Docker container images, not ML models specifically; it has no native concept of ML model versioning or metadata.
• B (SageMaker Marketplace model packages) is for discovering and purchasing pre-built third-party models, not for managing your own models.
• C (SageMaker ML Lineage Tracking) records the history of steps in an ML workflow (data, training jobs, experiments) for auditability - it tracks how a model was built, not versions of the model itself.

Memory tip: Think of the Model Registry as a "Git repository for your ML models" - just as Git versions your code, Model Registry versions your models with metadata, approval status, and deployment history.

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