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See the performance efficiency and cost optimization pillars in Machine Learning Lens.
Additionally this is an EC2 based right sizing best practices guide.
Overall, it's better to start small, then increase instance size as needed (as those that start large, never bother reduce the size), or apply auto scaling for SageMaker hosting.
Assuming a CPU ML predictions: When choosing ml.t2.medium instances the customer will need to keep an eye on the instance CPU credits. If they lack the knowledge, just start with M5.
answered 4 years ago
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Sorry for reviving an old question but where is it possible to view CPU credit usage when hosting Sagemaker endpoints on T instance types (specifically ml.t2.medium instances)? These instances don't appear in the EC2 console and the only CPU metric available in CloudWatch when clicking on the "View instance metrics" link under the "Monitor" section for an endpoint is CPUUtilization. Neither the CPUCreditUsage or CPUCreditBalance metrics seem to be available for Sagemaker endpoints even when using T instance types.