CloudWatch Metrics - Amazon SageMaker AI
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CloudWatch Metrics

You can use the built-in Amazon SageMaker Model Monitor container for CloudWatch metrics. When the emit_metrics option is Enabled in the baseline constraints file, SageMaker AI emits these metrics for each feature/column observed in the dataset in the following namespace:

  • For real-time endpoints: /aws/sagemaker/Endpoints/data-metric namespace with EndpointName and ScheduleName dimensions.

  • For batch transform jobs: /aws/sagemaker/ModelMonitoring/data-metric namespace with MonitoringSchedule dimension.

For numerical fields, the built-in container emits the following CloudWatch metrics:

  • Metric: Max → query for MetricName: feature_data_{feature_name}, Stat: Max

  • Metric: Min → query for MetricName: feature_data_{feature_name}, Stat: Min

  • Metric: Sum → query for MetricName: feature_data_{feature_name}, Stat: Sum

  • Metric: SampleCount → query for MetricName: feature_data_{feature_name}, Stat: SampleCount

  • Metric: Average → query for MetricName: feature_data_{feature_name}, Stat: Average

For both numerical and string fields, the built-in container emits the following CloudWatch metrics:

  • Metric: Completeness → query for MetricName: feature_non_null_{feature_name}, Stat: Sum

  • Metric: Baseline Drift → query for MetricName: feature_baseline_drift_{feature_name}, Stat: Sum