This document describes how to authenticate to Vertex AI Workbench programmatically.
For more information about Google Cloud authentication, see the authentication overview.
API access
Vertex AI Workbench supports programmatic access. How you authenticate to Vertex AI Workbench depends on how you access the API. You can access the API in the following ways:
Google Cloud CLI
When you use the gcloud CLI to access Vertex AI Workbench, you log in to the gcloud CLI with a Google Account, which provides the credentials used by the gcloud CLI commands.
If your organization's security policies prevent user accounts from having the required
permissions, you can impersonate a service account, either by using the
impersonate_service_account
property
or by using the
--impersonate-service-account
flag,
which affects only the command for which you use it.
For more information about using the gcloud CLI with Vertex AI Workbench, see the gcloud CLI reference pages.
REST
You can authenticate to Vertex AI Workbench from the command line by using Application Default Credentials. For more information, see Authenticate using REST.
If you want to use the API without using a client library, you can use Google's authentication library for your programming language. Alternatively, you can implement authentication in your code.
Access control in Vertex AI Workbench
When you grant roles to a principal, always grant roles with only the required permissions; granting broader roles, such as basic roles, violates the principle of least privilege.
For more information about the roles for Vertex AI Workbench, see Managed notebooks access control. For more information about Identity and Access Management (IAM) and authorization, see IAM overview.
What's next
- Learn more about Google Cloud authentication.
- See a list of authentication use cases.
- Grant a principal access to a managed notebooks instance.
- Grant a principal access to JupyterLab.