AWS Certified Machine Learning – Specialty — Question 53

A Machine Learning Specialist is building a model that will perform time series forecasting using Amazon SageMaker. The Specialist has finished training the model and is now planning to perform load testing on the endpoint so they can configure Auto Scaling for the model variant.
Which approach will allow the Specialist to review the latency, memory utilization, and CPU utilization during the load test?

Answer options

• A. Review SageMaker logs that have been written to Amazon S3 by leveraging Amazon Athena and Amazon QuickSight to visualize logs as they are being produced.
• B. Generate an Amazon CloudWatch dashboard to create a single view for the latency, memory utilization, and CPU utilization metrics that are outputted by Amazon SageMaker.
• C. Build custom Amazon CloudWatch Logs and then leverage Amazon ES and Kibana to query and visualize the log data as it is generated by Amazon SageMaker.
• D. Send Amazon CloudWatch Logs that were generated by Amazon SageMaker to Amazon ES and use Kibana to query and visualize the log data.

Correct answer: B

Explanation

The correct answer is B because Amazon CloudWatch dashboards are designed specifically to visualize metrics such as latency, memory utilization, and CPU utilization in a unified view, making it easier to monitor performance during load testing. Options A, C, and D involve additional steps or tools that are not necessary for directly monitoring these metrics, making them less efficient for this specific task.