MLS-C01 · Question #42
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…
The correct answer is B. Generate an Amazon CloudWatch dashboard to create a single view for the latency, memory. While indeed true that Cloudwatch does not have metrics for memory utilization by default, you can achieve by installing ClouldWatch agent on the EC2. The EC2 used by Sagemaker is pre- installed with Cloudwatch Agent…
Question
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?
Options
- AReview SageMaker logs that have been written to Amazon S3 by leveraging Amazon Athena and
- BGenerate an Amazon CloudWatch dashboard to create a single view for the latency, memory
- CBuild custom Amazon CloudWatch Logs and then leverage Amazon ES and Kibana to query and
- DSend Amazon CloudWatch Logs that were generated by Amazon SageMaker to Amazon ES and
How the community answered
(48 responses)- A2% (1)
- B90% (43)
- C2% (1)
- D6% (3)
Explanation
While indeed true that Cloudwatch does not have metrics for memory utilization by default, you can achieve by installing ClouldWatch agent on the EC2. The EC2 used by Sagemaker is pre- installed with Cloudwatch Agent. https://docs.aws.amazon.com/sagemaker/latest/dg/monitoring-cloudwatch.html
Topics
Community Discussion
No community discussion yet for this question.