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Exam AWS Certified Machine Learning Engineer - Associate MLA-C01 All Questions

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Exam AWS Certified Machine Learning Engineer - Associate MLA-C01 topic 1 question 45 discussion

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.
Which solution will meet these requirements?

  • A. Use SageMaker Debugger to track the inferences and to report metrics. Create a custom rule to provide a notification when the threshold is breached.
  • B. Use SageMaker Debugger to track the inferences and to report metrics. Use the tensor_variance built-in rule to provide a notification when the threshold is breached.
  • C. Log all the endpoint invocation API events by using AWS CloudTrail. Use an Amazon CloudWatch dashboard for monitoring. Set up a CloudWatch alarm to provide notification when the threshold is breached.
  • D. Add the Invocations metric to an Amazon CloudWatch dashboard for monitoring. Set up a CloudWatch alarm to provide notification when the threshold is breached.
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Suggested Answer: C 🗳️

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a4002bd
Highly Voted 1 month, 1 week ago
Selected Answer: C
I pick C. The company needs to implement a solution to record and monitor all the API call events for the SageMaker endpoint. Its needs to RECORD all events.
upvoted 6 times
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lyndonZhao
Most Recent 2 weeks, 6 days ago
Selected Answer: D
CloudWatch Invocations metric: This metric tracks the number of API calls made to a SageMaker endpoint. By adding this metric to a CloudWatch dashboard and setting up an alarm, you can monitor the number of API calls and receive notifications when the threshold is breached.
upvoted 1 times
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Saransundar
1 month ago
Selected Answer: C
SageMaker endpoint API calls → Record with CloudTrail → Monitor metrics in CloudWatch → CloudWatch alarm for notifications
upvoted 1 times
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