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NEWS · COMPANIES · #1726

Amazon outlines multi-tenant reference architecture for SageMaker HyperPod on EKS

AWS describes a reference architecture for using Amazon SageMaker HyperPod with Amazon EKS to let multiple teams share GPU clusters while preserving isolation, fair resource quotas, and per-team cost allocation. The design uses AWS IAM Identity Center for authentication, per-team SageMaker AI domains and Kubernetes namespaces for isolation, HyperPod Task Governance for quotas, and HyperPod Observability for monitoring.

KEY POINTS

  1. AWS describes a reference architecture for using Amazon SageMaker HyperPod with Amazon EKS to let multiple teams share GPU clusters while preserving isolation, fair resource quotas, and per-team cost allocation.
  2. The design uses AWS IAM Identity Center for authentication, per-team SageMaker AI domains and Kubernetes namespaces for isolation, HyperPod Task Governance for quotas, and HyperPod Observability for monitoring.
  3. This matters because it gives enterprises a tested blueprint to share expensive GPU infrastructure securely and fairly while enabling per-team cost visibility and operational independence.

WHY IT MATTERS

This matters because it gives enterprises a tested blueprint to share expensive GPU infrastructure securely and fairly while enabling per-team cost visibility and operational independence.

SOURCES & TIMELINE

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AWS MACHINE LEARNING FIRST-PARTY
Share GPU clusters across teams with isolation and fairness using Amazon SageMaker HyperPod

Multiple teams within the same company increasingly need shared access to expensive GPU clusters for their generative AI operations, while maintaining isolation boundaries, resource fairness, and operational independence. Consider a data science team training large language models, a computer vision group running inference workloads, and a research team experimenting with new model architectures. All of them might ne…

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