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Answer: Enable Amazon SageMaker logging and monitoring to collect logs and metrics from the machine learning environment.
In a machine learning environment, enabling Amazon SageMaker logging and monitoring to collect logs and metrics is crucial for identifying potential security events. This will provide visibility into the machine learning process and enable the setup of alerts based on specific criteria. While options B, C, and D are important for monitoring the machine learning environment, they do not directly address the comprehensive monitoring and alerting aspect of the question.
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Your company is implementing a new machine learning model using Amazon SageMaker. Which of the following steps should be taken to ensure comprehensive monitoring and alerting for security events in the machine learning environment?
A
Enable Amazon SageMaker logging and monitoring to collect logs and metrics from the machine learning environment.
B
Monitor the performance metrics of the machine learning model, such as accuracy and inference time, to identify potential issues.
C
Implement AWS CloudTrail and AWS Config to log API calls and configuration changes in the machine learning environment.
D
Set up Amazon CloudWatch alarms to monitor the usage of Amazon SageMaker resources and generate alerts based on predefined thresholds.
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