1. Unified Credential Brokering for GCP AI Services with Workload Identity Pool


    In Google Cloud Platform (GCP), Workload Identity Pools are a way to create a pool of identities that can be used by external workloads to directly assume identities in your GCP project. This is useful for scenarios where, for example, you have services running in another cloud provider or on-premises that need to authenticate to GCP to access GCP AI Services or other GCP resources.

    With Workload Identity Pools, you no longer need to manage service account keys for these external workloads; instead, they can leverage short-lived, automatically rotated tokens to authenticate. They do this by assuming an identity from a pool that you've authorized to make this cross-cloud brokering possible.

    To set up unified credential brokering for GCP AI Services with a Workload Identity Pool, you need to perform the following steps using Pulumi:

    1. Create a Workload Identity Pool.
    2. Configure Identity Providers for the pool (allows workloads from AWS, Azure, or services that support OpenID Connect).
    3. Create Workload Identity Pool providers for each identity provider you want to federate with GCP.
    4. Grant IAM roles to each workload identity in the pool, providing them with access to the resources they need.

    The following Pulumi program in Python outlines steps 1 and 3, using resources from the pulumi_gcp package. It assumes you want to federate with an AWS identity.

    import pulumi import pulumi_gcp as gcp # Create a new Workload Identity Pool. identity_pool = gcp.iam.WorkloadIdentityPool("my-identity-pool", description="Identity pool for accessing GCP AI services", display_name="My Workload Identity Pool", disabled=False ) # Create the Workload Identity Pool AWS provider. # This links the AWS account and the Workload Identity Pool in GCP, # so AWS workloads can assume GCP identities. identity_pool_provider = gcp.iam.WorkloadIdentityPoolProvider("my-identity-pool-provider", workload_identity_pool_id=identity_pool.id, display_name="My Workload Identity AWS Provider", description="AWS provider for my workload identity pool", disabled=False, aws=gcp.iam.WorkloadIdentityPoolProviderAwsArgs( account_id="123456789012" # The AWS Account ID ) ) # IAM roles can now be granted to specific identities within the pool, # for example, giving access to GCP AI services. # Example: # - The role `roles/aiplatform.user` could be granted to an identity in # the identity pool to give access to AI Platform resources. # Don't forget to export the Workload Identity Pool id and provider name so that # they can be used programmatically outside of Pulumi if necessary. pulumi.export('identity_pool_id', identity_pool.id) pulumi.export('identity_pool_provider_name', identity_pool_provider.name)

    This program sets up the core infrastructure for federating AWS identities with GCP but does not handle the actual permissions delegations that allow access to specific GCP resources such as the AI Platform. You would need to assign IAM roles to the identities within the pool to authorize access to GCP resources. This assignment can also be managed using Pulumi.

    Understanding how Workload Identity Federation works and its configuration requirements will help you set it up according to your organization's security and compliance needs. Please refer to GCP's Workload Identity Federation documentation for more detailed information and examples.