AWS sagemaker documentation change
Summary
Updated documentation to clarify metric capture granularity (team-level aggregates and task-specific breakdowns) and corrected a GitHub repository link
Security assessment
The change adds clarity about reporting granularity but does not address security vulnerabilities. The GitHub link update appears to be a repository name correction without security implications.
Diff
diff --git a/sagemaker/latest/dg/sagemaker-hyperpod-usage-reporting.md b/sagemaker/latest/dg/sagemaker-hyperpod-usage-reporting.md index 34934bdcf..598ea13e2 100644 --- a//sagemaker/latest/dg/sagemaker-hyperpod-usage-reporting.md +++ b//sagemaker/latest/dg/sagemaker-hyperpod-usage-reporting.md @@ -9 +9 @@ PrerequisitesReports typesReports formats and time rangeIllustrative use cases -Usage reporting in SageMaker HyperPod EKS-orchestrated clusters provides granular visibility into compute resource consumption. The capability allows organizations to implement transparent cost attribution, allocating cluster costs to teams, projects, or departments based on their actual usage. By tracking metrics such as GPU/CPU hours, and Neuron Core utilization over time, usage reporting complements HyperPod's [Task Governance](./sagemaker-hyperpod-eks-operate-console-ui-governance.html) functionality, ensuring fair cost distribution in shared multi-tenant clusters by: +Usage reporting in SageMaker HyperPod EKS-orchestrated clusters provides granular visibility into compute resource consumption. The capability allows organizations to implement transparent cost attribution, allocating cluster costs to teams, projects, or departments based on their actual usage. By tracking metrics such as GPU/CPU hours, and Neuron Core utilization - captured in _both team-level aggregates and task-specific breakdowns_ \- usage reporting complements HyperPod's [Task Governance](./sagemaker-hyperpod-eks-operate-console-ui-governance.html) functionality, ensuring fair cost distribution in shared multi-tenant clusters by: @@ -68 +68 @@ Using the Python script provided in [Generate reports](./sagemaker-hyperpod-usag -You can configure the historical window to extend beyond the default 180-day maximum when setting up the reporting infrastructure. For more information on configuring the data retention period, see [Install Usage Report Infrastructure using CloudFormation](https://github.com/awslabs/private-sagemaker-hyperpod-usage-report-staging/blob/main/README.md#install-usage-report-infrastructure-using-cloudformation). +You can configure the historical window to extend beyond the default 180-day maximum when setting up the reporting infrastructure. For more information on configuring the data retention period, see [Install Usage Report Infrastructure using CloudFormation](https://github.com/awslabs/sagemaker-hyperpod-usage-report/blob/main/README.md#install-usage-report-infrastructure-using-cloudformation).