AWS Certified Machine Learning Engineer - Associate MLA-C01 — Topic 1 Question 109

Question

An ML engineer has deployed an Amazon SageMaker model to a serverless endpoint in production. The model is invoked by the InvokeEndpoint API operation. The model's latency in production is higher than the baseline latency in the test environment. The ML engineer thinks that the increase in latency is because of model startup time. What should the ML engineer do to confirm or deny this hypothesis?

Accepted Answer

Correct answer: D. The correct answer is D. Option D: Enable Amazon CloudWatch metrics. Observe the ModelLoadingWaitTime metric in the SageMaker namespace. Amazon SageMaker builds, trains and deploys machine learning models in a fully managed service. Amazon CloudWatch collects metrics, logs and alarms to monitor and react to operational health.

AWS Certified Machine Learning Engineer - Associate MLA-C01 — Question 109