Question 24
Domain 3: Deployment and Orchestration of ML WorkflowsA company needs an AWS solution that will automatically create versions of ML models as the models are created. Which solution will meet this requirement?
Correct answer: D
Explanation
Amazon SageMaker Model Registry is designed to "automatically create versions of ML models" and track them as they are produced. It provides a central catalog for model metadata, versioning, and approval workflows, which fits the requirement to create versions as models are created.
Why each option is right or wrong
A. Amazon Elastic Container Registry (Amazon ECR)
Amazon ECR stores container images, not ML model versions or model governance records.
B. Model packages from Amazon SageMaker Marketplace
SageMaker Marketplace focuses on discovering and using packaged models, not versioning your newly created models.
C. Amazon SageMaker ML Lineage Tracking
ML Lineage Tracking records relationships among datasets, jobs, and models, but is not the model version registry.
D. Amazon SageMaker Model Registry
Amazon SageMaker Model Registry is the service that records model packages in a central catalog and assigns each new model package version as models are registered, which is the AWS-native mechanism for tracking ML model versions. In SageMaker, model package groups can contain multiple versions, and each registration creates a new numbered version (for example, Version 1, Version 2), supporting lifecycle tracking and approval states under the SageMaker API and console workflow.