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:
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Amazon SageMaker AI JupyterLab
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Code Editor, based on Code-OSS, Visual Studio Code - Open Source
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Studio Classic
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Notebook instance
Customizing your application includes:
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Installing custom packages
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Configuring extensions
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Preloading datasets
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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.
Understanding built-in and default lifecycle configurations
There are two types of lifecycle configurations in Studio:
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Built-in LCC: Built-in LCC is controlled by the administrator, always runs when a space starts, and resolves dynamically from the domain settings at launch time. When an administrator updates the built-in LCC at the domain level, all spaces automatically pick up the new LCC on their next launch without requiring any user action.
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Default LCC: The default LCC is pre-selected for the user at the space level and persists until the user explicitly changes it. Updating the domain-level default LCC does not affect running spaces until they are restarted.
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.
