Q: 2
A company has trained and deployed an ML model by using Amazon SageMaker. The company needs
to implement a solution to record and monitor all the API call events for the SageMaker endpoint.
The solution also must provide a notification when the number of API call events breaches a
threshold.
Use SageMaker Debugger to track the inferences and to report metrics. Create a custom rule to
provide a notification when the threshold is breached.
Which solution will meet these requirements?
Options
Discussion
Option D is the best fit. SageMaker automatically exports the Invocations metric to CloudWatch, so you just need to visualize and alarm on it. Debugger isn't meant for tracking endpoint API calls like this, pretty sure about D unless I'm missing something obvious.
Anyone else see this phrased similarly in the official practice tests? The Invocations metric is mentioned a lot in the AWS docs, and using CloudWatch alarms feels like standard AWS exam logic here.
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