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Create an instance with third party credentialsPreview
This feature is subject to the "Pre-GA Offerings Terms" in the General Service Terms section of the Service Specific Terms. Pre-GA features are available "as is" and might have limited support. For more information, see the launch stage descriptions.
This page describes how to create a Vertex AI Workbench instance with third party credentials.
OverviewYou can create and manage Vertex AI Workbench instances with third party credentials provided by Workforce Identity Federation. Workforce Identity Federation uses your external identity provider (IdP) to grant a group of users access to Vertex AI Workbench instances through a proxy.
Access to a Vertex AI Workbench instance is granted by assigning a workforce pool principal to the Vertex AI Workbench instance's service account.
Before you beginIn the Google Cloud console, on the project selector page, select or create a Google Cloud project.
Note: If you don't plan to keep the resources that you create in this procedure, create a project instead of selecting an existing project. After you finish these steps, you can delete the project, removing all resources associated with the project.Make sure that billing is enabled for your Google Cloud project.
Enable the Notebooks API.
In the Google Cloud console, on the project selector page, select or create a Google Cloud project.
Note: If you don't plan to keep the resources that you create in this procedure, create a project instead of selecting an existing project. After you finish these steps, you can delete the project, removing all resources associated with the project.Make sure that billing is enabled for your Google Cloud project.
Enable the Notebooks API.
To ensure that your workforce pool principal has the necessary permissions to create a Vertex AI Workbench instance, ask your administrator to grant your workforce pool principal the Notebooks Admin (roles/notebooks.admin
) IAM role on the project. For more information about granting roles, see Manage access to projects, folders, and organizations.
Your administrator might also be able to give your workforce pool principal the required permissions through custom roles or other predefined roles.
Required roles for using third party credentialsYour workforce pool principal needs access to your Vertex AI Workbench instance's service account, with specific permissions.
To ensure that the workforce pool principal has the necessary permissions to use a Vertex AI Workbench instance with third party credentials, ask your administrator to grant the workforce pool principal the following IAM roles on the service account that you'll specify when you create your instance:
roles/iam.serviceAccountTokenCreator
)roles/iam.serviceAccountUser
)For more information about granting roles, see Manage access to projects, folders, and organizations.
Your administrator might also be able to give the workforce pool principal the required permissions through custom roles or other predefined roles.
Create the instance using third party credentialsTo ensure that your Vertex AI Workbench instance contains a byoid.googleusercontent.com
domain, you must do one of the following:
Create the instance by using the Google Cloud Workforce Identity Federation console.
Use the enable_third_party_identity
flag when you create your instance.
You can create a Vertex AI Workbench using third party credentials by using the Google Cloud console or the gcloud CLI:
ConsoleSign in to the Google Cloud console using a workforce pool provider.
In the Google Cloud console, go to the Instances page.
Click add_box Create new.
In the New instance dialog, click Advanced options.
In the Create instance dialog, in the IAM and security section, do the following:
Make sure Service account is selected.
Clear Use default Compute Engine service account, and then, in the Service account email field, enter the service account email address that is associated with your workforce principal.
Click Create.
Vertex AI Workbench creates an instance and automatically starts it. When the instance is ready to use, Vertex AI Workbench activates an Open JupyterLab link.
Follow the IAM guide for authenticating the gcloud CLI with a workforce identity pool.
--enable-third-party-identity
Before using any of the command data below, make the following replacements:
INSTANCE_NAME
: the name of your Vertex AI Workbench instance; must start with a letter followed by up to 62 lowercase letters, numbers, or hyphens (-), and cannot end with a hyphenPROJECT_ID
: your project IDLOCATION
: the zone where you want your instance to be locatedVM_IMAGE_PROJECT
: the ID of the Google Cloud project that VM image belongs to, in the format: projects/IMAGE_PROJECT_ID
VM_IMAGE_NAME
: the full image name; to find the image name of a specific version, see Find the specific versionMACHINE_TYPE
: the machine type of your instance's VMMETADATA
: custom metadata to apply to this instance; for example, to specify a post-startup-script, you can use the post-startup-script
metadata tag, in the format: "--metadata=post-startup-script=gs://BUCKET_NAME/hello.sh"
SERVICE_ACCOUNT_EMAIL
: the service account email address that is associated with your workforce principalExecute the following command:
Linux, macOS, or Cloud Shell Note: Ensure you have initialized the Google Cloud CLI with authentication and a project by running either gcloud init; or gcloud auth login and gcloud config set project.gcloud workbench instances create INSTANCE_NAME \ --project=PROJECT_ID \ --location=LOCATION \ --vm-image-project=VM_IMAGE_PROJECT \ --vm-image-name=VM_IMAGE_NAME \ --machine-type=MACHINE_TYPE \ --metadata=METADATA \ --service-account-email=SERVICE_ACCOUNT_EMAILWindows (PowerShell) Note: Ensure you have initialized the Google Cloud CLI with authentication and a project by running either gcloud init; or gcloud auth login and gcloud config set project.
gcloud workbench instances create INSTANCE_NAME ` --project=PROJECT_ID ` --location=LOCATION ` --vm-image-project=VM_IMAGE_PROJECT ` --vm-image-name=VM_IMAGE_NAME ` --machine-type=MACHINE_TYPE ` --metadata=METADATA ` --service-account-email=SERVICE_ACCOUNT_EMAILWindows (cmd.exe) Note: Ensure you have initialized the Google Cloud CLI with authentication and a project by running either gcloud init; or gcloud auth login and gcloud config set project.
gcloud workbench instances create INSTANCE_NAME ^ --project=PROJECT_ID ^ --location=LOCATION ^ --vm-image-project=VM_IMAGE_PROJECT ^ --vm-image-name=VM_IMAGE_NAME ^ --machine-type=MACHINE_TYPE ^ --metadata=METADATA ^ --service-account-email=SERVICE_ACCOUNT_EMAIL
For more information about the command for creating an instance from the command line, see the gcloud CLI documentation.
Vertex AI Workbench creates an instance and automatically starts it. When the instance is ready to use, Vertex AI Workbench activates an Open JupyterLab link in the Google Cloud console.
Access Jupyterlab with third party credentialsYour new Vertex AI Workbench instance creates two separate proxy URLs with the following domains:
byoid.googleusercontent.com
: This domain can only be used by users authenticating with a workforce identity pool. Its value is stored in your instance's metadata field proxy-byoid-url
. This metadata value activates an Open JupyterLab link in the Google Cloud Workforce Identity Federation console (console.cloud.google/
).
googleusercontent.com
: This domain can only be used by users authenticating with the default Google's First Party Authentication. Its value is stored in your instance's metadata field proxy-url
. This metadata value activates an Open JupyterLab link in the Google Cloud console (console.cloud.google.com
).
Except as otherwise noted, the content of this page is licensed under the Creative Commons Attribution 4.0 License, and code samples are licensed under the Apache 2.0 License. For details, see the Google Developers Site Policies. Java is a registered trademark of Oracle and/or its affiliates.
Last updated 2025-07-02 UTC.
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