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Configure a space

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Configure a space - Amazon SageMaker AI

After you create a JupyterLab space, you can configure it to do the following:

  • Change the instance type.

  • Change the storage volume.

  • (Admin set up required) Use a custom image.

  • (Admin set up required) Use a lifecycle configuration.

  • (Admin set up required) Attach a custom Amazon EFS.

Important

You must stop the JupyterLab space every time you configure it. Use the following procedure to configure the space.

To configure a space
  1. Within Studio, navigate to the JupyterLab application page.

  2. Choose the name of the space.

  3. (Optional) For Image, specify an image that your administrator provided to customize your environment.

    Important

    Custom IAM policies that allow Studio users to create spaces must also grant permissions to list images (sagemaker: ListImage) to view custom images. To add the permission, see Add or remove identity permissions in the AWS Identity and Access Management User Guide.

    AWS managed policies for Amazon SageMaker AI that give permissions to create SageMaker AI resources already include permissions to list images while creating those resources.

  4. (Optional) For Space Settings, specify the following:

    • Storage (GB) – Up to 100 GB or the amount that your administrator configured for the space.

    • Lifecycle Configuration – A lifecycle configuration that your administrator provides.

    • Attach custom EFS filesystem – An Amazon EFS to which your administrator provides access.

  5. Choose Run space.

When you open the JupyterLab application, your space has the updated configuration.

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