Vertex AI Workbench is a component of Vertex AI. For information on all Vertex AI releases, see the Vertex AI release notes.
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November 20, 2024
M126 release
The M126 release of Vertex AI Workbench user-managed notebooks includes the following:
- Upgraded JupyterLab to 3.6.8.
- One or more framework versions have reached their end of patch and support dates. To view end of patch and support dates, see Supported framework versions. To create an instance using an image family that has reached its end of patch and support date, see Create an instance after end of patch and support date.
The M126 release of Vertex AI Workbench managed notebooks includes the following:
- Upgraded JupyterLab to 3.6.8.
M126 release
The M126 release of Vertex AI Workbench instances includes the following:
- Preview: JupyterLab 4+ is available on new Vertex AI Workbench instances. To try it, select JupyterLab 4 when you create your instance.
- Upgraded JupyterLab to 3.6.8.
September 26, 2024
M125 release
The M125 release of Vertex AI Workbench user-managed notebooks includes the following:
- Patched a vulnerability with
adm
anddocker
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
anddocker
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
anddocker
permissions when the instance's root access isn't enabled.
September 10, 2024
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.
August 20, 2024
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.
August 19, 2024
The ability to create a Vertex AI Workbench instance based on a custom container is now generally available. Only custom containers derived from the Google-provided base container are supported. For more information, see Create an instance using a custom container.
August 08, 2024
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.
July 24, 2024
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.
July 16, 2024
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.
June 21, 2024
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.
June 07, 2024
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.
June 03, 2024
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.
May 17, 2024
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.
April 29, 2024
M120 release
The M120 release of Vertex AI Workbench managed notebooks includes the following:
- Minor bug fixes for the
libcurl
package.
April 25, 2024
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.
March 29, 2024
M119 release
The M119 release of Vertex AI Workbench user-managed notebooks includes the following:
- Fixed an issue wherein Dataproc extensions caused JupyterLab to crash when remote kernels weren't available.
March 18, 2024
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.
February 28, 2024
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.
February 08, 2024
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.
January 19, 2024
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.
January 16, 2024
Vertex AI Workbench managed notebooks is deprecated. On January 30, 2025, support for managed notebooks will end and the ability to create managed notebooks instances will be removed. Existing instances will continue to function but patches, updates, and upgrades won't be available. To continue using Vertex AI Workbench, you can migrate your managed notebooks instances to Vertex AI Workbench instances.
Vertex AI Workbench user-managed notebooks is deprecated. On January 30, 2025, support for user-managed notebooks will end and the ability to create user-managed notebooks instances will be removed. Existing instances will continue to function but patches, updates, and upgrades won't be available. To continue using Vertex AI Workbench, you can migrate your user-managed notebooks instances to Vertex AI Workbench instances.
December 14, 2023
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.
November 16, 2023
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.
October 10, 2023
M112 release
The M112 release of Vertex AI Workbench user-managed notebooks includes the following:
- Miscellaneous bug fixes and improvements.
September 25, 2023
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.
September 18, 2023
Debian 10 and Python 3.7 images have reached their end of patch and support life for Vertex AI Workbench managed notebooks and user-managed notebooks. Debian 11 and Python 3.10 images are available.
September 14, 2023
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.
August 10, 2023
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.
TensorFlow 2.9 user-managed instances are deprecated.
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.
July 19, 2023
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.
June 26, 2023
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.
May 04, 2023
M108 release
The M108 release of Vertex AI Workbench user-managed notebooks includes the following:
- Miscellaneous software updates.
April 13, 2023
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.
April 06, 2023
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.
March 31, 2023
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
)
- TensorFlow 2.11 CPU (
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
)
- TensorFlow 2.6 CPU (
Jupyter-related libraries have been moved to a different Conda environment, separate from the one containing machine learning frameworks and base software libraries.
March 27, 2023
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
toINFO
.
March 16, 2023
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
andgateway-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.
TensorFlow Enterprise 2.1 has reached the end of its support period. See Version details.
February 21, 2023
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.
February 09, 2023
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.
January 30, 2023
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.
December 15, 2022
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.
December 09, 2022
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.
November 08, 2022
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.
Fixed a server-side request forgery (SSRF) vulnerability. Previous versions of managed notebooks and user-managed notebooks instances still contain the vulnerability. It is recommended that you migrate your data to a new instance.
October 25, 2022
The v1beta1
version of the Notebooks API is scheduled for removal no earlier than January 16, 2023. After this date, you must use Notebooks API v1
to manage Vertex AI Workbench resources.
October 18, 2022
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.
September 20, 2022
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.
Fixed a server-side request forgery (SSRF) vulnerability. Previous versions of managed notebooks and user-managed notebooks instances still contain the vulnerability. It is recommended that you migrate your data to a new instance.
August 17, 2022
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.
May 27, 2022
M93 release
The M93 release of Vertex AI Workbench managed notebooks includes the following:
- Fixed a bug that prevented kernels from shutting down properly in Vertex AI Workbench managed notebooks.
May 12, 2022
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.
- Fixed an issue that caused Spark server networking errors when using Dataproc Serverless Spark and VPC Peering.
April 06, 2022
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.
October 11, 2021
Vertex AI Workbench is now available in Preview. Vertex AI Workbench is a notebook-based development environment for the entire data science workflow.
The Notebooks product and all existing Notebooks instances are now part of Vertex AI Workbench as user-managed notebooks.
September 10, 2021
Due to a recent change, the iam.serviceAccounts.actAs
permission on the specified service account for the notebook instance is required for users to continue to have access to their notebook instances. The Google internal Inverting Proxy server that provides access to notebook instances now verifies that this permission is present before allowing users access to the JupyterLab URL. The JupyterLab URL this update covers is:
*.notebooks.googleusercontent.com
This update only applies to notebook instances in Single User mode and verifies that the assigned single user is authorized to execute code inside the notebook instance. Notebook instances running in Service Account or Project Editor mode already perform this verification via the Inverting Proxy server.
July 26, 2021
If using proxy single-user mode, Notebooks API now verifies if the specified user (proxy-user-mail
) has Service Account permissions on the Service Account. This check is performed during instance creation and registration.
June 18, 2021
Support for Compute Reservations. Notebooks API allows the use of Compute Reservations during instance creation.
March 26, 2021
Cross Project Service Account is supported for user-managed notebooks.
March 04, 2021
New Notebooks instances add labels for VM image (goog-caip-notebook
) and volume (goog-caip-notebook-volume
).
February 01, 2021
Notebooks Terraform Module supports Notebooks API v1
January 23, 2021
VPC-SC for Notebooks (now known as user-managed notebooks) is now Generally Available.
Notebooks API supports Shielded VM configuration.
September 21, 2020
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)
March 31, 2020
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.
February 04, 2020
VPC Service Controls now supports AI Platform Notebooks. Learn how to use a notebook instance within a service perimeter. This functionality is in beta.
February 03, 2020
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.
September 12, 2019
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).
September 09, 2019
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.
July 12, 2019
R upgraded to version 3.6.
R Notebooks are no longer dependent on a Conda environment.
June 03, 2019
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.
March 01, 2019
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.