AWS Certified Machine Learning Engineer – Associate (MLA-C01) — Question 139

A company has an existing Amazon SageMaker model (v1) on a production endpoint. The company develops a new model version (v2) and needs to test v2 in production before substituting v2 for v1.

The company needs to implement a solution to minimize the risk of v2 generating incorrect output in production. The solution must prevent any disruption of production traffic during the change to v2.

Which solution will meet these requirements?

Answer options

• A. Create a second production variant for v2. Assign 1% of the traffic to v2 and 99% of the traffic to v1. Collect all the output of v2 in an Amazon S3 bucket. If v2 performs as expected, switch all the traffic to v2.
• B. Create a second production variant for v2. Assign 10% of the traffic to v2 and 90% of the traffic to v1. Collect all the output of v2 in an Amazon S3 bucket. If v2 performs as expected, switch all the traffic to v2.
• C. Deploy v2 to a new endpoint. Turn on data capturing for the production endpoint. Write a script to pass 100% of input data to v2. If v2 performs as expected, deactivate the v1 endpoint and direct the traffic to v2.
• D. Deploy v2 into a shadow variant that samples 100% of the inference requests. Collect all the output in an Amazon S3 bucket. If v2 performs as expected, promote v2 to production.

Correct answer: D

Explanation

Option D is correct because deploying v2 into a shadow variant allows for real-time testing without affecting production traffic, capturing all inference requests for analysis. Options A and B involve splitting traffic, which introduces risk if v2 underperforms. Option C requires complete rerouting of traffic to v2, which could cause disruptions if v2 does not perform as expected.