Use JupyterLab notebooks

Prior reading: Overview of cloud app types

Purpose: This document provides additional information about using JupyterLab Compute Engine apps in Workbench.

Introduction

The JupyterLab app is one of the cloud app options available in Workbench. Vertex AI apps were deprecated in favor of JupyterLab apps in January 2025. If you're still working with Vertex AI apps, please see Migrating existing Vertex AI JupyterLab apps.

Installed software

The initial Workbench JupyterLab app image includes the following software versions:

• Ubuntu 22.04
• Python 3.10
• CUDA 11.8, cuDNN 8.9.6
• PyTorch 2.0.1
• TensorFlow 2.14.0
• R 4.4.2
• Tidyverse 2.2.1
• JupyterLab 4.3.1

Create a JupyterLab Compute Engine app

For a step-by-step guide to creating a JupyterLab Compute Engine app using the Workbench - R, PyTorch, TensorFlow image, see Create a new cloud app.

Specify a container image as the basis for a notebook app

Alternatively, instead of using the Workbench image for your JupyterLab app, you can specify a container image as the base image.

Any base image can be used. To learn more about building and uploading custom container images, see Create container images in a workspace.

Migrating existing Vertex AI JupyterLab apps

Verily Workbench does not persist the boot or data disks attached to app instances once they are deleted. If you have important data or notebooks in your app instance, make sure to preserve them in a workspace bucket. You can do this in several different ways.

• Workbench automounts your workspace Cloud Storage (GCS) buckets in app environments, so you can directly copy or move files to these buckets as if they were part of the local file system.

• You can also use the gcloud SDK — which is pre-installed for Workbench apps - to copy files to your workspace buckets. You can do this via the gcloud storage command (or the older gsutil utility). Click on a GCS bucket in a workspace's Resources tab to view and copy its gs:// URI from the right-hand panel.

Use of rsync to back up files

You may want to consider using the rsync utility to back up your files, especially if you're making changes at both the source and target, or doing periodic copies of new work.

rsync is available as a local command. Additionally, the gcloud storage command supports rsync and cp, as does gsutil.

Further migration details for the end of life for existing Vertex AI JupyterLab apps are in progress.

Known issues with JupyterLab apps

The following issues are known and will be addressed in future releases:

• The docker container runtime is not available.
• nvidia-smi does not list GPU memory usage of individual processes.