1. Service Account-Based Authentication for AI Platform Notebooks.

    Python

    To configure a Google Cloud AI Platform Notebook instance with service account-based authentication using Pulumi, you'll use resources from the Pulumi Google Cloud Provider. To achieve this, you would generally follow these steps:

    1. Create a new service account or use an existing one that the notebook instance will use to interact with Google Cloud services.
    2. Assign appropriate roles to the service account to define the permissions it should have.
    3. Create a new AI Platform Notebook instance and associate it with the service account.

    Let's go through the Pulumi code that accomplishes the above steps in Python. Below is a program that sets up a Google Cloud AI Platform Notebook instance with a new service account and grants it the editor role. Please note that in a real-world scenario, the permissions should be the least privilege necessary, not just the editor role.

    import pulumi import pulumi_gcp as gcp # Create a new service account for the AI Notebook notebook_service_account = gcp.serviceaccount.Account("notebook-service-account", account_id="notebook-account", display_name="Notebook Service Account" ) # Grant the service account the editor role (replace with appropriate roles) # It's important to limit the service account's permissions to the least required editor_role_binding = gcp.projects.IAMMember("editor-role-binding", member=pulumi.Output.concat("serviceAccount:", notebook_service_account.email), role="roles/editor" ) # Create a new AI Platform Notebook instance with the service account notebook_instance = gcp.notebooks.Instance("notebook-instance", location="us-west1", # Replace with the desired location service_account=notebook_service_account.email, instance_owners=[notebook_service_account.email], # Add service account as an owner machine_type="n1-standard-1", # Replace with the desired machine type ) pulumi.export('notebook_instance_name', notebook_instance.name) pulumi.export('notebook_instance_url', notebook_instance.proxy_uri)

    In this program:

    • We create a new service account using the gcp.serviceaccount.Account resource. This service account will be used to authenticate and access other Google Cloud services from the AI Platform Notebook.
    • We assign the editor role to the service account using gcp.projects.IAMMember. Be sure to replace roles/editor with the specific roles required for your use case.
    • We create a gcp.notebooks.Instance resource to deploy a new AI Platform Notebook instance. We pass the service account's email to the service_account property of the Notebook instance. This will make the notebook authenticate API requests using this service account.
    • We export the Notebook instance name and URL, which can be used to access the Notebook after deployment.

    In a more secure and production-ready environment, you would want to scope down the permissions of the service account to only what's necessary for your notebook instance to function as expected.

    Remember to replace placeholder values like us-west1 and n1-standard-1 with the actual values that correspond to your desired configuration. Secure your service account by following the principle of least privilege and only granting it the roles and permissions it needs to operate.