An ML engineer has developed a binary classification model outside of Amazon SageMaker. The ML engineer needs to make the model accessible to a SageMaker Canvas user for additional tuning.The model artifacts are stored in an Amazon S3 bucket. The ML engineer and the Canvas user are part of the same SageMaker domain.Which combination of requirements must be met so that the ML engineer can share the model with the Canvas user? (Choose two.)

The Canvas user must have permissions to access the S3 bucket where the model artifacts are stored.

The model must be registered in the SageMaker Model Registry.

The ML engineer and the Canvas user must be in separate SageMaker domains.

The Canvas user must have permissions to access the S3 bucket where the model artifacts are stored.

The model must be registered in the SageMaker Model Registry.

The ML engineer must host the model on AWS Marketplace.

The ML engineer must deploy the model to a SageMaker endpoint.

A company has developed a new ML model. The company requires online model validation on 10% of the traffic before the company fully releases the model in production. The company uses an Amazon SageMaker endpoint behind an Application Load Balancer (ALB) to serve the model.Which solution will set up the required online validation with the LEAST operational overhead?

Use production variants to add the new model to the existing SageMaker endpoint. Set the variant weight to 0.1 for the new model. Monitor the number of invocations by using Amazon CloudWatch.

Use production variants to add the new model to the existing SageMaker endpoint. Set the variant weight to 1 for the new model. Monitor the number of invocations by using Amazon CloudWatch.

Create a new SageMaker endpoint. Use production variants to add the new model to the new endpoint. Monitor the number of invocations by using Amazon CloudWatch.

Configure the ALB to route 10% of the traffic to the new model at the existing SageMaker endpoint. Monitor the number of invocations by using AWS CloudTrail.

Amazon MLA-C01 Practice Test 3 - Free Online Exam Prep & Questions

A company needs to create a central catalog for all the company's ML models. The models are in AWS accounts where the company developed the models initially. The models are hosted in Amazon Elastic Container Registry (Amazon ECR) repositories.

Which solution will meet these requirements?

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Amazon MLA-C01 Practice Test 3

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