Amazon SageMaker Studio - Amazon SageMaker AI

Amazon SageMaker Studio

Important

As of November 30, 2023, the previous Amazon SageMaker Studio experience is now named Amazon SageMaker Studio Classic. The following section is specific to using the updated Studio experience. For information about using the Studio Classic application, see Amazon SageMaker Studio Classic.

Amazon SageMaker Studio is the latest web-based experience for running ML workflows. Studio offers a suite of integrated development environments (IDEs). These include Code Editor, based on Code-OSS, Visual Studio Code - Open Source, a new JupyterLab application, RStudio, and Amazon SageMaker Studio Classic. For more information, see Applications supported in Amazon SageMaker Studio.

The new web-based UI in Studio is faster and provides access to all SageMaker AI resources, including jobs and endpoints, in one interface. ML practitioners can also choose their preferred IDE to accelerate ML development. A data scientist can use JupyterLab to explore data and tune models. In addition, a machine learning operations (MLOps) engineer can use Code Editor with the pipelines tool in Studio to deploy and monitor models in production.

The previous Studio experience is still being supported as Amazon SageMaker Studio Classic. Studio Classic is the default experience for existing customers, and is available as an application in Studio. For more information about Studio Classic, see Amazon SageMaker Studio Classic. For information about how to migrate from Studio Classic to Studio, see Migration from Amazon SageMaker Studio Classic.

Studio offers the following benefits:

  • A new JupyterLab application that has a faster start-up time and is more reliable than the existing Studio Classic application. For more information, see SageMaker JupyterLab.

  • A suite of IDEs that open in a separate tab, including the new Code Editor, based on Code-OSS, Visual Studio Code - Open Source application. Users can interact with supported IDEs in a full screen experience. For more information, see Applications supported in Amazon SageMaker Studio.

  • Access to all of your SageMaker AI resources in one place. Studio displays running instances across all of your applications. 

  • Access to all training jobs in a single view, regardless of whether they were scheduled from notebooks or initiated from Amazon SageMaker JumpStart.

  • Simplified model deployment workflows and endpoint management and monitoring directly from Studio. You don't need to access the SageMaker AI console.

  • Automatic creation of all configured applications when you onboard to a domain. For information about onboarding to a domain, see Amazon SageMaker AI domain overview.

  • An improved JumpStart experience where you can discover, import, register, fine tune, and deploy a foundation model. For more information, see SageMaker JumpStart pretrained models.

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