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Amazon EKS

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Headlines · 3

  1. AWS details multi-tenant GPU cluster sharing on SageMaker HyperPod

    An AWS Machine Learning Blog post lays out a reference architecture for letting multiple teams share a single Amazon SageMaker HyperPod (EKS) GPU cluster while preserving isolation and fairness. It uses AWS IAM Identity Center for centralized authentication (federating with Microsoft Entra ID via SCIM provisioning and SAML 2.0), per-team SageMaker AI domains and execution roles, and Kubernetes namespaces for workload isolation. HyperPod Task Governance handles fair resource allocation, namespace-level cost allocation provides per-team chargeback visibility, and storage is split across FSx for Lustre or OpenZFS directories and S3 buckets.

    AWS Machine Learning Blog · 🔥 4
  2. Best practices for Amazon SageMaker HyperPod administration and governance

    An AWS Machine Learning Blog post explains how to administer Amazon SageMaker HyperPod clusters through Amazon SageMaker Unified Studio while preserving underlying governance controls. It lays out four layers of control — organization, project, cluster, and workload — and covers designing identity, capacity, and observability policies across them, plus a "connection contract" record for each approved project-to-cluster connection.

    AWS Machine Learning Blog · 🔥 0
  3. SageMaker Studio can now manage HyperPod Spaces without the CLI

    AWS says users can now create, configure, start, stop and open Amazon SageMaker Spaces on Amazon SageMaker HyperPod EKS clusters directly from the SageMaker Studio UI, instead of relying on the HyperPod CLI or kubectl. A new IDE and Notebooks tab on the cluster detail page offers a guided form and a searchable Spaces table, with browser access to JupyterLab or Code Editor and remote VS Code access over SSH-over-SSM. AWS says Karpenter over-provisioning can cut Space startup from 5–7 minutes to roughly 30–40 seconds.

    AWS Machine Learning Blog · 🔥 0

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