Applications supported in 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 supports the following applications:
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Code Editor, based on Code-OSS, Visual Studio Code - Open Source– Code Editor offers a lightweight and powerful integrated development environment (IDE) with familiar shortcuts, terminal, and advanced debugging capabilities and refactoring tools. It is a fully managed, browser-based application in Studio. For more information, see Code Editor in Amazon SageMaker Studio.
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Amazon SageMaker Studio Classic– Amazon SageMaker Studio Classic is a web-based IDE for machine learning. With Studio Classic, you can build, train, debug, deploy, and monitor your machine learning models. For more information, see Amazon SageMaker Studio Classic.
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JupyterLab–JupyterLab offers a set of capabilities that augment the fully managed notebook offering. It includes kernels that start in seconds, a pre-configured runtime with popular data science, machine learning frameworks, and high performance block storage. For more information, see SageMaker JupyterLab.
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Amazon SageMaker Canvas– With SageMaker Canvas, you can use machine learning to generate predictions without writing code. With Canvas, you can chat with popular large language models (LLMs), access ready-to-use models, or build a custom model that's trained on your data. For more information, see Amazon SageMaker Canvas.
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RStudio– RStudio is an integrated development environment for R. It includes a console and syntax-highlighting editor that supports running code directly. It also includes tools for plotting, history, debugging, and workspace management. For more information, see RStudio on Amazon SageMaker.