---
format: "aidr-story-markdown/v1"
id: "45c08c2987280b22121bd85d5776b17c816de8bf137a918cfd430414e7ce985c"
canonical_url: "https://aidr.today/45c08c29?lang=en"
title: "Manage Amazon SageMaker HyperPod Spaces directly from SageMaker Studio"
lang: "en"
requested_lang: "en"
available_langs: ["en","vi"]
translation_fallback: null
fallback_fields: []
published_at: "2026-10-06T15:47:02.000Z"
category: "Tools"
topics: ["amazon","coding","devtools"]
source_urls: ["https://aws.amazon.com/blogs/machine-learning/manage-amazon-sagemaker-hyperpod-spaces-directly-from-sagemaker-studio/"]
summary: "Data scientists and ML engineers can now create, configure, start, stop, and open Amazon SageMaker Spaces on SageMaker HyperPod EKS clusters directly from SageMaker Studio using JupyterLab and Code Editor environments."
---

# Manage Amazon SageMaker HyperPod Spaces directly from SageMaker Studio

> [Open the canonical story](<https://aidr.today/45c08c29?lang=en>)

**Published:** 2026-10-06T15:47:02.000Z
**Category:** Tools
**Topics:** amazon, coding, devtools

## Summary

Data scientists and ML engineers can now create, configure, start, stop, and open Amazon SageMaker Spaces on SageMaker HyperPod EKS clusters directly from SageMaker Studio using JupyterLab and Code Editor environments\.

## Sources

- [Story source](<https://aws.amazon.com/blogs/machine-learning/manage-amazon-sagemaker-hyperpod-spaces-directly-from-sagemaker-studio/>)