Notebooks instances are Deep Learning VM Images instances with JupyterLab notebook environments enabled and ready for use. For updates about Deep Learning VM releases, see the Deep Learning VM release notes.
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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:
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 support
March 04, 2021
New Notebooks instances add labels for VM image (
goog-caip-notebook) and volume (
February 01, 2021
Notebooks Terraform Module supports Notebooks API v1
January 23, 2021
VPC-SC for Notebooks is now Generally Available
Notebooks API supports Shielded VM configuration
September 21, 2020
AI Platform Notebooks now supports E2 machine types.
The following new regions have been added:
March 31, 2020
AI Platform 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 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.