Vertex AI Workbench release notes

M125 release

The M125 release of Vertex AI Workbench user-managed notebooks includes the following:

• Patched a vulnerability with adm and docker permissions when the instance's root access isn't enabled.

The M125 release of Vertex AI Workbench managed notebooks includes the following:

• Patched a vulnerability with adm and docker permissions when the instance's root access isn't enabled.

M125 release

The M125 release of Vertex AI Workbench instances includes the following:

• bigframes 1.9.0 is now available in all environments except TensorFlow.
• Fixed a regression introduced in M124 where Conda was getting downgraded to an older version.
• Patched a vulnerability with adm and docker permissions when the instance's root access isn't enabled.

The ability to back up and restore data on a Vertex AI Workbench instance is now available in Preview. For more information, see Back up and restore an instance.

M124 release

The M124 release of Vertex AI Workbench user-managed notebooks includes the following:

• Pytorch 2.3.0 with CUDA 12.1 and Python 3.10 user-managed notebooks instances are now available.
• Fixed a bug that prevented kernels from appearing when the Cloud Resource Manager API is turned off and Dataproc is enabled.

M124 release

The M124 release of Vertex AI Workbench managed notebooks includes the following:

• Fixed a bug that prevented kernels from appearing when the Cloud Resource Manager API is turned off and Dataproc is enabled.

M124 release

The M124 release of Vertex AI Workbench instances includes the following:

• Fixed a bug that prevented kernels from appearing when the Cloud Resource Manager API is turned off and Dataproc is enabled.
• Spark notebooks on Dataproc: The Serverless Spark runtime template creation screen now has an easy-to-use UI for configuring resource allocation, autoscaling, and GPU settings.

M123 release

The M123 release of Vertex AI Workbench managed notebooks includes the following:

• Fixed a bug that caused conflicting permissions with the Jupyter user and google-sudoers.
• Updated Nvidia drivers to version 550.90.07 to fix vulnerabilities.

M123 release

The M123 release of Vertex AI Workbench user-managed notebooks includes the following:

• Fixed a bug that caused conflicting permissions with the Jupyter user and google-sudoers.
• Fixed a bug for custom container instances using a disabled root.

M123 release

The M123 release of Vertex AI Workbench instances includes the following:

• Fixed a bug that caused conflicting permissions with the Jupyter user and google-sudoers.

M122 release

The M122 release of Vertex AI Workbench user-managed notebooks includes the following:

• Updated Nvidia drivers to version 550.90.07 to fix vulnerabilities.

M122 release

The M122 release of Vertex AI Workbench instances includes the following:

• Updated Nvidia drivers to version 550.90.07 to fix vulnerabilities.

You can now create a Vertex AI Workbench instance based on a custom container. This feature is available in Preview. Only custom containers derived from the Google-provided base container are supported. For more information, see Create an instance using a custom container.

You can now use Workforce Identity Federation with Vertex AI Workbench instances in Preview. Workforce Identity Federation lets you create and manage Vertex AI Workbench instances with credentials provided by an external identity provider (IdP). For more information, see Create an instance with third party credentials.

M121 release

The M121 release of Vertex AI Workbench user-managed notebooks includes the following:

• Updated Nvidia drivers to 550.54.15 to fix an issue where Nvidia drivers failed to install on startup after Debian 11 images upgraded kernel to linux-image-5.10.0-29-cloud-amd64.
• The linux-headers-cloud-amd64 metapackage is now installed for faster driver recompiling on kernel upgrades.
• TensorFlow 2.6 CPU and GPU images are deprecated. There will be no further updates to these images in future releases.

The M121 release of Vertex AI Workbench managed notebooks includes the following:

• Updated the R CPU kernel from R 4.3 to R 4.4.

M121 release

The M121 release of Vertex AI Workbench instances includes the following:

• Updated Nvidia drivers to 550.54.15 to fix an issue where Nvidia drivers failed to install on startup after Debian 11 images upgraded kernel to linux-image-5.10.0-29-cloud-amd64.
• The linux-headers-cloud-amd64 metapackage is now installed for faster driver recompiling on kernel upgrades.

M120 release

The M120 release of Vertex AI Workbench managed notebooks includes the following:

• Minor bug fixes for the libcurl package.

M120 release

The M120 release of Vertex AI Workbench user-managed notebooks includes the following:

• Upgraded TensorFlow 2.15 user-managed notebooks to TensorFlow 2.15.1.
• Minor bug fixes for the libcurl package.

M120 release

The M120 release of Vertex AI Workbench instances includes the following:

• Minor bug fixes for the libcurl package.

M118 release

The M118 release of Vertex AI Workbench user-managed notebooks includes the following:

• PyTorch 2.1.0 with CUDA 12.1 and Python 3.10 user-managed notebooks instances are now available.
• PyTorch 2.2.0 with CUDA 12.1 and Python 3.10 user-managed notebooks instances are now available.
• Updated Nvidia drivers of older user-managed notebooks images to R535.

The M118 release of Vertex AI Workbench managed notebooks includes the following:

• Updated Nvidia drivers to R535, which fixed a bug where the latest PyTorch 2.0 kernel didn't work due to outdated drivers.

M118 release

The M118 release of Vertex AI Workbench instances includes the following:

• Updated Nvidia drivers to R535.

M117 release

The M117 release of Vertex AI Workbench instances includes the following:

• Removed the Cloud Storage browser in the left side pane in favor of the existing Mount shared storage button.

M116 release

The M116 release of Vertex AI Workbench user-managed notebooks includes the following:

• Updated custom container user-managed notebooks to use NVIDIA driver version 535.104.05.
• Fixed bugs in custom container user-managed notebooks where GPUs either wouldn't attach to the container properly, or detached after some time.

The M116 release of Vertex AI Workbench managed notebooks includes the following:

• Fixed a bug (present in versions M113 through M115) that prevented new local kernels from being usable.

M115 release

The M115 release of Vertex AI Workbench user-managed notebooks includes the following:

• Added support for TensorFlow 2.15 with Python 3.10 on Debian 11.
• Added support for TensorFlow 2.14 with Python 3.10 on Debian 11.

The M115 release of Vertex AI Workbench managed notebooks includes the following:

• Fixed the BigQuery connector within PySpark containers.

M115 release

The M115 release of Vertex AI Workbench instances includes the following:

• Added support for venv kernels.

M114 release

The M114 release of Vertex AI Workbench user-managed notebooks includes the following:

• Starting with this release, Python 3.7 is no longer available.
• Upgraded R to 4.3 on Debian 11 Python 3.10 instances.
• Upgraded JupyterLab to 3.6.6.

The M114 release of Vertex AI Workbench managed notebooks includes the following:

• Starting with this release, Python 3.7 is no longer available.
• Added new Dataproc extension for remote kernels.
• Upgraded JupyterLab to 3.6.6.
• Fixed an issue that sometimes prevented users from running or scheduling notebooks using a default kernel.

M113 release

The M113 release of Vertex AI Workbench instances includes the following:

• Added the Dataproc JupyterLab plugin to Vertex AI Workbench instances. To get started, see Create a Dataproc-enabled instance.
• When using an instance's Google Cloud CLI, gcloud config is preset with the following defaults:
  • project is set to your instance's project.
  • Your compute region is set to your instance's region.
  • Your Dataproc region is set to your instance's region.
• Fixed an issue that prevented Dataproc kernels from working.
• Fixed a CORS (cross-origin resource sharing) error.

M113 release

The M113 release of Vertex AI Workbench user-managed notebooks includes the following:

• Miscellaneous bug fixes and improvements in Python 3.10 notebooks.

M112 release

The M112 release of Vertex AI Workbench user-managed notebooks includes the following:

• Miscellaneous bug fixes and improvements.

Vertex AI Workbench instances are now generally available (GA). Vertex AI Workbench instances combine features from managed notebooks and user-managed notebooks to provide a robust data science solution. Supported features include:

• Idle timeout
• BigQuery and Cloud Storage integrations
• End-user and service account authentication
• VPC Service Controls
• Customer managed encryption keys (CMEK) and Cloud External Key Manager (Cloud EKM)
• Health status monitoring
• Scheduled notebook runs
• Dataproc integration

To get started, see Introduction to Vertex AI Workbench instances.

M111 release

The M111 release of Vertex AI Workbench instances includes the following:

• Miscellaneous software updates.

The M111 release of Vertex AI Workbench user-managed notebooks includes the following:

• PyTorch 2.0 user-managed notebooks instances now include PyTorch XLA 2.0.
• Miscellaneous software updates.

The M111 release of Vertex AI Workbench managed notebooks includes the following:

• Miscellaneous software updates.

M110 release

The M110 release of Vertex AI Workbench user-managed notebooks includes the following:

• Added support for TensorFlow 2.13 with Python 3.10 on Debian 11.
• Added support for TensorFlow 2.8 with Python 3.10 on Debian 11.
• Miscellaneous software updates.

The M110 release of Vertex AI Workbench managed notebooks includes the following:

• Increased shared memory size to available memory capacity.
• Added support for Python 3.10 on Debian 11.
  • Added support for PyTorch 2.0 with Python 3.10.

Vertex AI Workbench instances are now available in Preview. Vertex AI Workbench instances combine features from managed notebooks and user-managed notebooks to provide a robust data science solution. Supported features include:

• Idle timeout
• BigQuery and Cloud Storage integrations
• End-user and service account authentication
• VPC Service Controls
• Customer managed encryption keys (CMEK)
• Health status monitoring
• Run notebooks on a schedule
• Dataproc integration

To get started, see Introduction to Vertex AI Workbench instances.

M109 release

The M109 release of Vertex AI Workbench user-managed notebooks includes the following:

• PyTorch 2.0 with Python 3.10 and CUDA 11.8 user-managed notebooks instances are now available.
• Miscellaneous software updates.

The M109 release of Vertex AI Workbench managed notebooks includes the following:

• Fixed a bug that caused high cpu utilization due to excessive internal diagnostic tool processes.
• Fixed a bug that was showing incorrect kernel image icons in the Jupyterlab launcher.

M108 release

The M108 release of Vertex AI Workbench user-managed notebooks includes the following:

• Miscellaneous software updates.

M107 release

The M107 release of Vertex AI Workbench user-managed notebooks includes the following:

• Fixed a bug that displayed the wrong version of the JupyterLab user interface.
• Fixed a bug where a cron job for the diagnostic tool was added at every restart.
• Miscellaneous software updates.

M106 release

The M106 release of Vertex AI Workbench user-managed notebooks includes the following:

• Rolled back a previous change in which Jupyter dependencies were located in a separate Conda environment.
• Fixed a bug in which kernels used by notebooks did not contain the specified machine learning frameworks.
• Miscellaneous software updates.

M105 release

The M105 release of Vertex AI Workbench user-managed notebooks includes the following:

• The following user-managed notebooks images are now available with Python 3.10 on Debian 11:

  • TensorFlow 2.11 CPU (tf-2-11-cpu-debian-11-py310)
  • TensorFlow 2.11 GPU with Cuda 11.3 (tf-2-11-cu113-notebooks-debian-11-py310)
  • PyTorch 1.13 with Cuda 11.3 (pytorch-1-13-cu113-notebooks-debian-11-py310)
  • Base CPU (common-cpu-notebooks-debian-11-py310)
  • Base GPU with Cuda 11.3 (common-cu113-notebooks-debian11-py310)

• The following user-managed notebooks images are now available with Python 3.9 on Debian 11:

  • TensorFlow 2.6 CPU (tf-2-6-cpu-notebooks-debian-11-py39)
  • TensorFlow 2.6 GPU with Cuda 11.3 (tf-2-6-cu113-notebooks-debian-11-py39)

• Jupyter-related libraries have been moved to a different Conda environment, separate from the one containing machine learning frameworks and base software libraries.

M105 release

The M105 release of Vertex AI Workbench managed notebooks includes the following:

• Fixed an issue wherein a runtime with idle shutdown enabled doesn't detect activity and shuts down.
• Fixed an issue wherein the runtime data disk runs out of space and prevents access.
• Fixed an issue wherein end user credentials are not preserved after shutdown.
• Changed Health Agent logging levels from DEBUG to INFO.

M104 release

The M104 release of Vertex AI Workbench user-managed notebooks includes the following:

• Fixed a regression in which jupyter-user metadata was ignored.
• Enabled access to the Jupyter Gateway Client configuration by using the notebook-enable-gateway-client and gateway-client-url metadata tags.
• Added the following packages:
  • google-cloud-artifact-registry
  • google-cloud-bigquery-storage
  • google-cloud-language
  • keyring
  • keyrings.google-artifactregistry-auth
• Fixed a bug in which curl could not find the right SSL certificate path by default.

M104 update

This update of the M104 release of Vertex AI Workbench managed notebooks includes the following:

• Fixed a bug where local and remote kernels are not displayed. This happens when remote kernels are not accessible.
• Minor bug fixes and improvements.

M104 release

The M104 release of Vertex AI Workbench managed notebooks includes the following:

• Added a fix for a security vulnerability in single-user managed notebooks instances.
• Made enhancements to the network selection user experience in the managed notebooks executor.
• Minor bug fixes and improvements.

M103 release

The M103 release of Vertex AI Workbench user-managed notebooks includes the following:

• Fixed a bug in which a warning tells the user to run jupyter lab build when creating a new instance.
• Upgraded PyTorch to 1.13.1.
• Minor bug fixes and improvements.

M102 release

The M102 release of Vertex AI Workbench user-managed notebooks includes the following:

• TensorFlow 2.11 is now available.
• PyTorch 1.13 is now available.
• Regular security patches and package upgrades.

M101 release

The M101 release of Vertex AI Workbench includes the following:

• TensorFlow patch version upgrades:
  • From 2.8.3 to 2.8.4.
  • From 2.9.2 to 2.9.3.
  • From 2.10.0 to 2.10.1.
• TensorFlow 1.15 on Vertex AI Workbench is now deprecated.
• Added *.notebooks.cloud.google.com as part of the domains required for users to access Notebooks API. Removed *.datalab.cloud.google.com.
• Regular security patches and package upgrades.

M100 release

The M100 release of Vertex AI Workbench includes the following:

• Fixed a bug that prevented an instance with a GPU from starting.
• Regular package updates.
• Miscellaneous bug and display fixes.

M98 release

The M98 release of Vertex AI Workbench managed notebooks includes the following:

• Upgraded Go from 1.16.5 to 1.19.2.
• Upgraded R from 4.1 to 4.2.
• Upgraded JupyterLab from 3.2 to 3.4.
• Miscellaneous bug and display fixes.
• Added a fix for the BigQuery SQL editor to run queries correctly in non-US locations.
• Regular package updates.

Learn more about managed notebooks versions.

M96 release

The M96 release of Vertex AI Workbench managed notebooks includes the following:

• Fixed a problem where users were not able to save large Notebooks.
• Fixed a display issue when using JupyterLab's simple interface.
• Improved timeout behavior switch hardware operations.
• Improved error messaging when a service account cannot access the Runtime.
• Security fixes.
• Regular package refreshment and bug fixes.

Learn more about managed notebooks versions.

M95 release

The M95 release of Vertex AI Workbench managed notebooks includes the following:

• Fixed a bug where users were regularly getting a 502 error when trying to access JupyterLab.
• Fixed a bug where opening an instance in Single User mode slowed the start of an instance.
• Fixed a bug where a managed notebooks instance was not starting after adding a GPU.
• Fixed bugs on the Serverless Spark form input.
• Improved the ActivityLog refresh after Serverless Spark creation.
• Fixed a bug related to the display of materialized views in BigQuery.
• Refreshed the JupyterLab interface with an improved Google-specific theme.
• Fixed a bug related to viewing Cloud Storage buckets and folders with large numbers of objects.
• Regular package refreshment and bug fixes.

Learn more about managed notebooks versions.

M93 release

The M93 release of Vertex AI Workbench managed notebooks includes the following:

M91 release

The M91 release of Vertex AI Workbench managed notebooks includes the following:

• Log streaming to the consumer project via Logs Viewer is now supported.
• Added the net-tools package.
• Regular package refreshments and bug fixes.

Vertex AI Workbench is generally available (GA). Vertex AI Workbench is a single notebook surface for all your data science needs that lets you access BigQuery data and Cloud Storage from within JupyterLab, execute notebook code in Vertex AI custom training and Spark, use custom containers, manage costs with idle timeout, and secure your instances with VPC Service Controls and customer managed encryption keys (CMEK).

Features supported include:

• Google-managed instances and the latest GPU support
• Idle shutdown for managed notebooks instances
• Custom containers
• End-user and service account authentication
• Native plug-ins for BigQuery and Cloud Storage
• In-notebook Spark connect to Dataproc clusters
• Jobs support via the managed notebooks executor on Vertex AI custom training and Spark
• One-click deploy for NGC containers
• VPC Service Controls
• Customer managed encryption keys (CMEK)

The Vertex AI Workbench managed notebooks executor is generally available (GA). Use the executor to run notebook files on a schedule or as a one-time execution. You can use parameters in your execution to make specific changes to each run. For example, you might specify a different dataset to use, change the learning rate on your model, or change the version of the model. For more information, see Run notebook files with the executor.

Vertex AI Workbench is now available in Preview. Vertex AI Workbench is a notebook-based development environment for the entire data science workflow.

Support for Compute Reservations. Notebooks API allows the use of Compute Reservations during instance creation.

Cross Project Service Account is supported for user-managed notebooks.

Notebooks Terraform Module supports Notebooks API v1

Notebooks API supports Shielded VM configuration.

AI Platform Notebooks (now known as user-managed notebooks) API is now Generally Available. The API now includes an isUpgradable endpoint and adds manual and auto-upgrade functionality to notebooks instances created using the API.

Cloud Audit Logging for AI Platform Notebooks (now known as user-managed notebooks) is now Generally Available.

Granular IAM permissions for AI Platform Notebooks (now known as user-managed notebooks) is now Generally Available.

AI Platform Notebooks now supports E2 machine types.

The following new regions have been added:

• europe-west2 (London, UK)
• europe-west3 (Frankfurt, Germany)
• europe-west6 (Zürich, Switzerland)

AI Platform Notebooks (now known as user-managed notebooks) is now Generally Available. Some integrations with and specific features of AI Platform Notebooks are still in beta, such as Virtual Private Cloud Service Controls, Identity and Access Management (IAM) roles, and AI Platform Notebooks API.

VPC Service Controls now supports AI Platform Notebooks. Learn how to use a notebook instance within a service perimeter. This functionality is in beta.

AI Platform Notebooks now supports Access Transparency. Access Transparency provides you with logs of actions that Google staff have taken when accessing your data. To learn more about Access Transparency, see the Overview of Access Transparency.

You can now use customer-managed encryption keys (CMEK) to protect data on the boot disks of your AI Platform Notebooks (now known as user-managed notebooks) VM instances. CMEK in AI Platform Notebooks is generally available. For more information, see Using customer-managed encryption keys (CMEK).

AI Platform Notebooks now provides more ways for you to customize your network settings, encrypt your notebook content, and grant access to your notebook instance. These options are available when you create a notebook.

Now you can implement AI Platform Notebooks using custom containers. Use a Deep Learning Containers image or create a derivative container of your own, then create a new notebook instance using your custom container.

You can now create AI Platform Notebooks instances with R and core R packages installed. Learn how to install R dependencies, and read guides for using R with BigQuery in AI Platform Notebooks and using R and Python in the same notebook.

AI Platform Notebooks is now available in beta. AI Platform Notebooks enables you to create and manage virtual machine (VM) instances that are pre-packaged with JupyterLab and a suite of deep learning software.

Visit the AI Platform Notebooks overview and the guide to creating a new notebook instance to learn more.