Lifecycle configurations within Amazon SageMaker Studio - Amazon SageMaker AI
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Lifecycle configurations within Amazon SageMaker Studio

Lifecycle configurations (LCCs) are scripts that administrators and users can use to automate the customization of the following applications within your Amazon SageMaker Studio environment:

  • Amazon SageMaker AI JupyterLab

  • Code Editor, based on Code-OSS, Visual Studio Code - Open Source

  • Studio Classic

  • Notebook instance

Customizing your application includes:

  • Installing custom packages

  • Configuring extensions

  • Preloading datasets

  • Setting up source code repositories

Users create and attach built-in lifecycle configurations to their own user profiles. Administrators create and attach default or built-in lifecycle configurations at the domain, space, or user profile level.

Important

Amazon SageMaker Studio first runs the built-in lifecycle configuration and then runs the default LCC. Amazon SageMaker AI won't resolve package conflicts between the user and administrator LCCs. For example, if the built-in LCC installs python3.11 and the default LCC installs python3.12, Studio installs python3.12.