AWS Certified Machine Learning Engineer – Associate (MLA-C01) — Question 115

A company has an ML model that is deployed to an Amazon SageMaker endpoint for real-time inference. The company needs to deploy a new model. The company must compare the new model’s performance to the currently deployed model’s performance before shifting all traffic to the new model.

Which solution will meet these requirements with the LEAST operational effort?

Answer options

• A. Deploy the new model to a separate endpoint. Manually split traffic between the two endpoints.
• B. Deploy the new model to a separate endpoint. Use Amazon CloudFront to distribute traffic between the two endpoints.
• C. Deploy the new model as a shadow variant on the same endpoint as the current model. Route a portion of live traffic to the shadow model for evaluation.
• D. Use AWS Lambda functions with custom logic to route traffic between the current model and the new model.

Correct answer: C

Explanation

The correct answer is C because deploying the new model as a shadow variant allows for real-time traffic evaluation with minimal operational effort. The other options require more complex setups, such as manual traffic splitting or the use of additional services like CloudFront or Lambda, which increase operational overhead.