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.

To follow step-by-step guidance for this task directly in the Google Cloud console, click Guide me:

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 Google Cloud project.

  4. Enable the Notebooks API.

    Enable the API

    5.

  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 Google Cloud project.

  7. Enable the Notebooks API.

    Enable the API

    8.

Create an instance

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

    Go to User-managed notebooks

  2. Click  Create new.

  3. For Name, enter my-instance.

  4. Click Create.

When you finish the tasks that are described in this document, you can avoid continued billing by deleting the resources that 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 a compute instance forcibly wipes the memory contents of your instance and resets the instance to its initial state. To learn more about how resetting an instance works, see Resetting an 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 reset.

  3. Click Reset, and then click Reset to confirm.

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, then delete the project.

If you used an existing Google Cloud project, then 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 row containing the instance that you want to delete.

  3. Click  Delete. (Depending on the size of your window, the Delete button might be in the  options menu.)

  4. To confirm, click Delete.

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