Hide machine learning tools and applications on a domain level - Amazon SageMaker AI

Hide machine learning tools and applications on a domain level

The following shows how to use the console to customize the applications and ML tools displayed in Studio on a domain level. For more information, see Hide machine learning tools and applications in the Amazon SageMaker Studio UI.

This feature is not available if Amazon SageMaker Studio Classic is set as your default experience.

To hide machine learning tools and applications Studio UI on a domain level (console)

  1. Open the Amazon SageMaker AI console at https://console.aws.amazon.com/sagemaker/.

  2. On the left navigation pane, choose Admin configurations.

  3. Under Admin configurations, choose domains.

  4. From the list of domains, choose the link to the domain you wish to edit.

  5. On the Domain details page, choose the App Configurations tab.

  6. In the SageMaker Studio section, choose Customize Studio UI.

  7. On the Customize Studio UI page you can hide applications and ML tools displayed in Studio by toggling them off.

    Note that not all ML features are available in all regions.

  8. Once you have reviewed your changes, choose Save.

Once completed, you will see a green banner containing a success message at the top of the page.

Note

To use this feature you may need to update to the latest AWS CLI version. For more information, see Installing or updating to the latest version of the AWS CLI.

You can use the AWS CLI to customize the applications and ML tools displayed in Studio on a domain level, using StudioWebPortalSettings. Use HiddenAppTypes to hide applications and HiddenMlTools to hide ML tools.

In the following example, SageMaker Canvas and Code Editor are being hidden for users in the domain domainId.

aws sagemaker update-domain \
  --domain-id domainId \
  --default-user-settings '{"StudioWebPortalSettings": {"HiddenAppTypes": ["Canvas", "CodeEditor"]}}'

Note that not all ML features are available in all AWS Regions.