Introduction to user-managed notebooks

Vertex AI Workbench user-managed notebooks isdeprecated. On April 14, 2025, support for user-managed notebooks ended and the ability to create user-managed notebooks instances was removed. Existing instances will continue to function until March 30, 2026, but patches, updates, and upgrades won't be available. To continue using Vertex AI Workbench, we recommend that youmigrate your user-managed notebooks instances to Vertex AI Workbench instances.

Vertex AI Workbench user-managed notebooks instanceslet you create and manage deep learning virtual machine(VM) instances that are prepackaged withJupyterLab.

User-managed notebooks instances havea preinstalled suite of deep learning packages,including support for the TensorFlow and PyTorchframeworks. You can configure either CPU-only or GPU-enabled instances.

Your user-managed notebooks instances are protectedby Google Cloudauthentication and authorization and are available by using auser-managed notebooks instance URL.User-managed notebooks instances also integrate withGitHub and can sync with a GitHub repository.

User-managed notebooks instances save youthe difficulty of creating andconfiguring aDeep Learning virtual machineby providing verified, optimized, and tested imagesfor your chosen framework.

Preinstalled software

You can configure a user-managed notebooks instanceto include the following:

• JupyterLab (see version details)

• Python 3, with key packages:

  • numpy
  • sklearn
  • scipy
  • pandas
  • nltk
  • pillow
  • fairness-indicators for TensorFlow 2.3 and 2.4user-managed notebooks instances
  • many others

• R version 4.x, with key packages:

  • xgboost
  • ggplot2
  • caret
  • nnet
  • rpy2 (an R package for accessing R in Python notebooks)
  • randomForest
  • many others

• Anaconda

• Nvidia packages with the latest Nvidia driver for GPU-enabled instances:

  • CUDA 11.x and 12.x
  • CuDNN 7.x
  • NCCL 2.x

JupyterLab version details

JupyterLab 3.x is preinstalled onnew user-managed notebooks instancesby default. For instances created beforetheM80 Deep Learning VMrelease,JupyterLab 1.x was preinstalled.

To create an earlier version of a user-managed notebooks instance,seeCreate a specific version of a user-managed notebooksinstance.

VPC Service Controls

VPC Service Controls provides additional security for youruser-managed notebooks instances.For more information, see theOverview ofVPC Service Controls. To useuser-managed notebooks within a service perimeter, seeUsea user-managed notebooks instance within a serviceperimeter.

Upgrades

You can upgrade your environment to use new capabilities and to benefit fromframework updates, package updates, and bug fixes. You canupgrade environments manually or through an automatic update setting.To learn more, seeUpgrade the environment ofa user-managed notebooks instance.

User-managed notebooks and Dataproc Hub

Dataproc Hub is a customizedJupyterHub server.Administrators can create Dataproc Hub instances that canspawn single-userDataproc clusters to hostuser-managed notebooks environments. For more information, seeConfigure Dataproc Hub.

User-managed notebooks and Dataflow

You can use user-managed notebooks within a pipeline,and then runthe pipeline onDataflow. For information abouthow to create anApache Beam user-managed notebooks instance that you can use withDataflow, seeDeveloping interactively with Apache Beamnotebooks.

Limitations

Consider the following limitations ofuser-managed notebooks when planning your project:

• User-managed notebooks instances are highlycustomizable and can beideal for users who need a lot of control over their environment.Therefore, user-managed notebooks instancescan require more time to set up and manage thanmanaged notebooks instances.Managed notebooks instances can bemore ideal for users who don't need a lot of control over their environment.For more information, seeIntroduction tomanaged notebooks.

• Third party JupyterLab extensions are not supported.

• The Dataproc JupyterLab plugin isn't supported foruser-managed notebooks, but you can use the plugin inVertex AI Workbench instances. SeeCreate aDataproc-enabledinstance.

• For Dataproc Hub user-managed notebooks instances,disabling file downloading from the JupyterLab user interfaceis not supported. User-managed notebooks instancesthat use the Dataproc Hub framework permit file downloading evenif you don't selectEnable file downloading from JupyterLab UIwhen you create the instance.

• When you useAccess Context ManagerandChrome Enterprise Premiumto protect managed notebooks instances withcontext-aware access controls, access is evaluated each timethe user authenticates to the instance. For example, accessis evaluated the first time the user accesses JupyterLab andwhenever they access it thereafter if their web browser'scookie has expired.

Pricing

Learn more about Vertex AI Workbenchpricing.