AWS Certified Machine Learning Engineer - Associate MLA-C01 — Topic 1 Question 219

Question

A company develops a recommendation model and hosts the model on an Amazon SageMaker AI endpoint. The model uses the SageMaker AI endpoint to perform near real-time inference to deliver personalized product recommendations to customers based on browsing history, purchase records, and in-app user interactions. After a major marketing campaign, the company observes a sharp drop in the model’s performance. The company needs a solution to proactively monitor, detect, and validate model performance before future marketing campaigns. Which solution will meet these requirements?

Accepted Answer

Correct answer: D. The correct answer is D. Option D: Use SageMaker Model Monitor to monitor constraints. Use Amazon CloudWatch Logs Insights to analyze error patterns. 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. This option meets the real-time / low-latency performance requirement.

AWS Certified Machine Learning Engineer - Associate MLA-C01 — Question 219