{"id":"12212391-6f83-4afd-8690-9b89f8665657","url":"https://api.tumn.com/news/12212391-6f83-4afd-8690-9b89f8665657","title":"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. Launch JupyterLab and Code Editor environments in a few clicks, without using command-line tools.","sections":[],"faq":[],"sources":[{"url":"https://aws.amazon.com/blogs/machine-learning/manage-amazon-sagemaker-hyperpod-spaces-directly-from-sagemaker-studio/","title":"AWS Machine Learning Blog","publishedAt":"2026-10-06T15:47:02.000Z"}],"author":"TUMN 큐레이션","aiAssisted":false,"reviewStatus":"automated","reviewNote":"원문 제목과 공개된 발췌를 인용하고 원문으로 연결합니다. 내용을 재작성하거나 요약하지 않았습니다.","publishedAt":"2026-10-06T15:47:02.000Z","modifiedAt":"2026-10-06T21:24:31.000Z","checkedAt":"2026-10-06T21:24:31.626Z","language":"ko","kind":"link","sourceLabel":"AI 공식","profile":null,"via":null,"formats":{"json":"https://api.tumn.com/news/12212391-6f83-4afd-8690-9b89f8665657.json","markdown":"https://api.tumn.com/news/12212391-6f83-4afd-8690-9b89f8665657.md"}}