A company is building a web-based AI application by using Amazon SageMaker. The application will provide the following capabilities and features: ML…

The Amazon SageMaker Model Registry is the purpose-built service for centrally cataloging, versioning, and managing machine learning models for deployment. The core organizational construct within the Model Registry is the "model package group" (or model group). A model group is used to collect and manage different versions of the same model. By registering each new model iteration as a new version within a specific model group, the company can track lineage, compare performance metrics, and manage the approval status for each version, fulfilling the requirement with the least operational overhead as it is a managed, integrated feature.

A. Create a separate Amazon Elastic Container Registry (Amazon ECR) repository for each model.

Amazon ECR is a registry for container images, not a model registry. This approach lacks the necessary governance, metadata, and versioning features specific to ML models.

B. Use Amazon Elastic Container Registry (Amazon ECR) and unique tags for each model version.

This is also incorrect as ECR is for container images. While tags provide a form of versioning for images, it does not provide the model-centric features of the SageMaker Model Registry.

D. Use the SageMaker Model Registry and unique tags for each model version.

While tags can be applied for metadata, the primary mechanism for cataloging and versioning models in the SageMaker Model Registry is the "model group," not tags. This option is less precise.

1. Amazon SageMaker Developer Guide: "With Amazon SageMaker Model Registry you can catalog models for production

manage model versions

associate metadata... You group model versions that you create in the model registry into model groups."

Source: AWS Documentation

Amazon SageMaker Developer Guide

"SageMaker Model Registry".

URL: https://docs.aws.amazon.com/sagemaker/latest/dg/model-registry.html

2. Amazon SageMaker Feature Page: "Amazon SageMaker Model Registry is a purpose-built tool that allows you to catalog your ML models... You can track model lineage

approve models for deployment

and deploy them from the registry..."

Source: AWS Documentation

Amazon SageMaker Features.

URL: https://aws.amazon.com/sagemaker/model-registry/

3. Amazon SageMaker API Reference: The CreateModelPackageGroup API call is used to "Creates a model package group. A model package group is a collection of model packages." This confirms that the group is the primary collection entity.

Source: AWS Documentation

Amazon SageMaker API Reference.

URL: https://docs.aws.amazon.com/sagemaker/latest/APIReference/APICreateModelPackageGroup.html