You are part of a machine learning team in a financial services company that builds a model that will perform time series forecasting of stock price movement using SageMaker. You and your team have finished training the model, and you are now ready to performance test your endpoint to get the best parameters for configuring auto-scaling for your model variant. How can you most efficiently review the latency, memory utilization, and CPU utilization during the load test?

Answer options:

A.Stream the SageMaker model variant CloudWatch logs to ElasticSearch. Then visualize and query the log data in a Kibana dashboard.
B.Create custom CloudWatch logs containing the metrics you wish to monitor, then stream the SageMaker model variant logs to ElasticSearch and visualize/query the log data in a Kibana dashboard.
C.Create a CloudWatch dashboard to show a view of the latency, memory utilization, and CPU utilization metrics of the SageMaker model variant.
D.Query the SageMaker model variant logs on S3 using Athena and leverage QuickSight to visualize the logs.

Correct Answer: C
Option A is incorrect. Using ElasticSearch and Kibana unnecessarily complicates the solution. A CloudWatch dashboard can show all of the metric data you need to evaluate your model variant.
Option B is incorrect. You don’t need to create custom CloudWatch logs with the metrics you wish to monitor. All of the metrics (latency, memory utilization, and CPU utilization) you wish to view are generated by CloudWatch by default. Also, using ElasticSearch and Kibana unnecessarily complicates the solution.
Option C is correct. The simplest approach is to leverage the CloudWatch dashboard feature since it generates all of the metrics (latency, memory utilization, and CPU utilization) you wish to view by default.
Option D is incorrect. Using Athena and QuickSight unnecessarily complicates the solution. A CloudWatch dashboard can show all of the metric data you need to evaluate your model variant.
References:
Please see the Amazon SageMaker developer guide titled Monitor Amazon SageMaker with Amazon CloudWatch (https://docs.aws.amazon.com/sagemaker/latest/dg/monitoring-cloudwatch.html),
The Amazon CloudWatch user guide titled Using Amazon CloudWatch Dashboards (https://docs.aws.amazon.com/AmazonCloudWatch/latest/monitoring/CloudWatch_Dashboards.html),
The Amazon CloudWatch user guide titled Creating a CloudWatch Dashboard (https://docs.aws.amazon.com/AmazonCloudWatch/latest/monitoring/create_dashboard.html)