Topic 1 Question 45
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?
Use SageMaker Debugger to track the inferences and to report metrics. Create a custom rule to provide a notification when the threshold is breached.
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.
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.
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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コメント(4)
- 正解だと思う選択肢: 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.
👍 6a4002bd2024/11/26 - 正解だと思う選択肢: C
SageMaker endpoint API calls → Record with CloudTrail → Monitor metrics in CloudWatch → CloudWatch alarm for notifications
👍 1Saransundar2024/12/05 - 正解だと思う選択肢: 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.
👍 1lyndonZhao2024/12/20
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