Upgrade the environment of a managed notebooks instance

Vertex AI Workbench managed notebooks is deprecated . On April 14, 2025, support for managed notebooks will end and the ability to create managed notebooks instances will be removed. Existing instances will continue to function but patches, updates, and upgrades won't be available. To continue using Vertex AI Workbench, we recommend that you migrate your managed notebooks instances to Vertex AI Workbench instances .

Vertex AI Workbench managed notebooks instances are Google-managed environments with integrations and features that help you set up and work in an end-to-end notebook-based production environment. This page describes how to upgrade the environment of a managed notebooks instance.

Upgrade methods

There is one way to upgrade a managed notebooks instance:

• Manual upgrade: If an existing managed notebooks instance meets the requirements for upgrading, you can upgrade the instance manually.

Requirements and limitations

Backward compatibility with your managed notebooks isn't guaranteed. Make a copy of your data before upgrading a managed notebooks instance.

To determine whether you can upgrade a specific managed notebooks instance, see the following requirements and limitations:

• The Notebooks API must be enabled in the instance's Google Cloud project . For more information, see List enabled services and Enable an API .

• After upgrading, an instance cannot be rolled back to the previous version.

• Instances that are version M112 or earlier use Python 3.7, and therefore can't be upgraded to a more recent version than M112. This is because M112 is the latest version to support Python 3.7.

How the upgrade works

Managed notebooks instances are dual-disk, with one boot disk and one data disk. The upgrade process upgrades the boot disk to a new image while preserving your data on the data disk.

Which components are upgraded

The following table shows which components of your managed notebooks instance are upgraded, which are preserved, and which need to be reinstalled.

Component	Upgrade result
Machine learning frameworks	Upgraded
Machine learning data	Preserved
Preinstalled Python dependencies	Upgraded
User-installed Python packages	Must be reinstalled
Preinstalled operating system packages	Upgraded
GPU drivers	Upgraded
Notebooks	Preserved
User configurations	Preserved

Before you begin

Before you upgrade, complete the following steps.

1. Check the release notes to learn about updates to newer versions.

2. Make a copy of your data as a backup.

Check for a newer version of your instance's environment

To check whether a newer version of your instance's environment is available, access your instance from the Google Cloud console.

1. In the Google Cloud console, go to the Managed notebookspage.

   Go to Managed notebooks

2. On the Managed notebookstab, "Upgrade available" will appear in each upgradeable instance's row. There will also be a message at the top saying how many notebooks have available upgrades.

Upgrade your instance's environment to a newer version

You can manually upgrade a managed notebooks instance in the Google Cloud console.

1. In the Google Cloud console, go to the Managed notebookspage.

   Go to Managed notebooks

2. If the instances that you want to upgrade aren't running, start the instances . Vertex AI Workbench can only upgrade instances when they're running.

3. If you want to upgrade all upgradeable managed notebooks instances, then on the Managed notebookstab, in the message at the top of the page, click the Upgrade allbutton. If there is no message at the top, then there are no managed notebooks instances that can be upgraded.

4. If you want to upgrade an individual notebook, then on the Managed notebookstab, select the managed notebooks instance that you want to upgrade. There will be an "Upgrade available" message in the instance's row.

5. Make sure you have made a copy of the data on your instance before continuing.

6. On the Managed notebookstab, click Upgrade.