쿠키 기본 설정 선택

당사는 사이트와 서비스를 제공하는 데 필요한 필수 쿠키 및 유사한 도구를 사용합니다. 고객이 사이트를 어떻게 사용하는지 파악하고 개선할 수 있도록 성능 쿠키를 사용해 익명의 통계를 수집합니다. 필수 쿠키는 비활성화할 수 없지만 '사용자 지정' 또는 ‘거부’를 클릭하여 성능 쿠키를 거부할 수 있습니다.

사용자가 동의하는 경우 AWS와 승인된 제3자도 쿠키를 사용하여 유용한 사이트 기능을 제공하고, 사용자의 기본 설정을 기억하고, 관련 광고를 비롯한 관련 콘텐츠를 표시합니다. 필수가 아닌 모든 쿠키를 수락하거나 거부하려면 ‘수락’ 또는 ‘거부’를 클릭하세요. 더 자세한 내용을 선택하려면 ‘사용자 정의’를 클릭하세요.

Receiving model logs and metrics

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Receiving model logs and metrics - AWS Clean Rooms
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To receive logs and metrics from custom model training or inference, members must have created an ML Configuration with a valid role that provides the necessary CloudWatch permissions (see Create a service role for custom ML modeling - ML Configuration).

System metric

System metrics for both training and inference, such as CPU and memory utilization, are published to all members in the collaboration with valid ML Configurations. These metrics can be viewed as the job progresses via CloudWatch Metrics in the /aws/cleanroomsml/TrainedModels or /aws/cleanroomsml/TrainedModelInferenceJobs namespaces, respectively.

Model logs

Access to the model logs is provided by the privacy configuration policy of each configured model algorithm. The model author sets the privacy configuration policy when associating a configured model algorithm (either via the console or the CreateConfiguredModelAlgorithmAssociation API) to a collaboration. Setting the privacy configuration policy controls which members can receive the model logs.

Additionally, the model author can set a filter pattern in the privacy configuration policy to filter log events. All logs that a model container sends to stdout or stderr and that match the filter pattern (if set), are sent to Amazon CloudWatch Logs. Model logs are available in CloudWatch log groups /aws/cleanroomsml/TrainedModels or /aws/cleanroomsml/TrainedModelInferenceJobs, respectively.

Custom defined metrics

When you configure a model algorithm (either via the console or the CreateConfiguredModelAlgorithm API), the model author can provide specific metric names and regex statements to search for in the output logs. These can be viewed as the job progresses via CloudWatch Metrics in the /aws/cleanroomsml/TrainedModels namespace. When associating a configured model algorithm, the model author can set an optional noise level in the metrics privacy configuration to avoid outputting raw data while still providing visibility into custom metric trends. If a noise level is set, the metrics are published at the end of the job rather than in real time.

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