Create a user-managed notebooks instance by using the Google Cloud console

Learn how to create a Vertex AI Workbench user-managed notebooks instance and open JupyterLab by using the Google Cloud console. This page also describes how to stop, start, reset, or delete a user-managed notebooks instance.


For step-by-step guidance on this task directly in Google Cloud console, click Guide me:

Guide me


The following sections take you through the same steps as clicking Guide me.

Before you begin

  1. Sign in to your Google Cloud account. If you're new to Google Cloud, create an account to evaluate how our products perform in real-world scenarios. New customers also get $300 in free credits to run, test, and deploy workloads.
  2. In the Google Cloud console, on the project selector page, select or create a Google Cloud project.

    Go to project selector

  3. Make sure that billing is enabled for your Cloud project. Learn how to check if billing is enabled on a project.

  4. Enable the Notebooks API.

    Enable the API

  5. In the Google Cloud console, on the project selector page, select or create a Google Cloud project.

    Go to project selector

  6. Make sure that billing is enabled for your Cloud project. Learn how to check if billing is enabled on a project.

  7. Enable the Notebooks API.

    Enable the API

Create an instance

  1. In the Google Cloud console, go to the User-managed notebooks page.

    Go to User-managed notebooks

  2. Click  New notebook, and then select Python 3.

  3. For Notebook name, enter my-instance.

  4. Click Create.

When you finish this tutorial, you can avoid continued billing by deleting the resources you created. For more information, see Clean up.

Open JupyterLab

After you create your instance, Vertex AI Workbench automatically starts the instance. When the instance is ready to use, Vertex AI Workbench activates an Open JupyterLab link.

  1. Next to your user-managed notebooks instance's name, click Open JupyterLab.

    Your user-managed notebooks instance opens JupyterLab.

Open a new notebook file

  1. Select File > New > Notebook.

  2. In the Select Kernel dialog, select Python 3, and then click Select.

  3. Your new notebook file opens.

Change the kernel

You can change the kernel of your JupyterLab notebook file from the menu or in the file.

  1. In JupyterLab, on the Kernel menu, click Change kernel.

  2. In the Select Kernel dialog, select another kernel to use and then click Select.

In the file

  1. In your JupyterLab notebook file, click the kernel name.

    The current kernel.

  2. In the Select Kernel dialog, select another kernel to use and then click Select.

Stop your instance

  1. In the Google Cloud console, go to the User-managed notebooks page.

    Go to User-managed notebooks

  2. Select the instance that you want to stop.

  3. Click  Stop.

Start your instance

  1. In the Google Cloud console, go to the User-managed notebooks page.

    Go to User-managed notebooks

  2. Select the instance that you want to start.

  3. Click  Start.

Reset your instance

Resetting an instance forcibly wipes the memory contents of your virtual machine (VM) and resets the VM to its initial state. To learn more, see Reset a VM.

  1. In the Google Cloud console, go to the User-managed notebooks page.

    Go to User-managed notebooks

  2. Select the instance that you want to reset.

  3. Click  Reset.

Clean up

To avoid incurring charges to your Google Cloud account for the resources used on this page, follow these steps.

If you created a new project to learn about Vertex AI Workbench user-managed notebooks and you no longer need the project, delete the project.

If you used an existing Google Cloud project, delete the resources you created to avoid incurring charges to your account:

  1. In the Google Cloud console, go to the User-managed notebooks page.

    Go to User-managed notebooks

  2. Select the instance that you want to delete.

  3. Click  Delete.

What's next