SageMaker HyperPod 管理与治理最佳实践
原标题：Best practices for Amazon SageMaker HyperPod administration and governance
AI 摘要
AWS 官方博客介绍 Amazon SageMaker HyperPod 的集群管理与治理最佳实践，重点解决多团队共享加速计算集群时的权限、容量分配与问责问题。文章提出组织、项目、集群、工作负载四层控制模型，并说明如何通过 SageMaker Unified Studio 将已批准的 HyperPod 集群接入项目，同时保留 IAM、EKS、Slurm 等底层治理控制。核心建议是将集群与稀缺加速器容量集中在指定容量账户中，用跨账户访问而非让各消费账户独立管理容量。
正文节选
Best practices for Amazon SageMaker HyperPod administration and governance Amazon SageMaker HyperPod gives machine learning (ML) teams access to large pools of accelerated compute for training and fine-tuning models. When several teams share one cluster, the technical setup is usually straightforward. The challenging part is governance. You must decide which teams can use the cluster, how much capacity each team gets, what happens when one team’s workload competes with another’s, and who is acco