1. Automated LLMs Access Management with GCP Workload Identity Pool


    To automate access management for large language models (LLMs) with Google Cloud Platform (GCP), we'll use GCP's Workload Identity Pools. Workload Identity Pools provide a way to create a pool of identities that can assume the roles necessary to access LLMs or other Google Cloud services. By integrating Workload Identity Pools into your access management system, you can enable applications running outside of Google Cloud (such as on-premises or on other clouds) to authenticate and access Google Cloud resources securely.

    First, we'll create a WorkloadIdentityPool to represent a pool of external identities from a non-Google Cloud provider. Then, we'll create a WorkloadIdentityPoolProvider to allow us to configure access for identities like AWS accounts or OIDC providers to assume Google Cloud roles. Finally, we'll set up IAM Policies to grant the necessary permissions for these identities to interact with LLMs or other services.

    Below is a Pulumi program in Python that sets up a WorkloadIdentityPool and a WorkloadIdentityPoolProvider. It also grants an IAM role to the workload identity pool to access LLM resources. Please adjust the workload_identity_pool_id, workload_identity_pool_provider_id, and the IAM role according to your needs.

    import pulumi import pulumi_gcp as gcp # Workload Identity Pool allows applications from other clouds or on-premises to access Google Cloud resources. workload_identity_pool = gcp.iam.WorkloadIdentityPool("my-llm-workload-identity-pool", workload_identity_pool_id="my-llm-workload-pool", display_name="My LLM Workload Identity Pool", description="Workload Identity Pool for LLM access management") # Workload Identity Pool Provider enables non-Google Cloud identities to be used in Workload Identity Pools. workload_identity_pool_provider = gcp.iam.WorkloadIdentityPoolProvider("my-llm-workload-identity-pool-provider", workload_identity_pool_id=workload_identity_pool.workload_identity_pool_id, display_name="My LLM Workload Identity Pool Provider", description="Workload Identity Pool Provider for LLM access management", oidc=gcp.iam.WorkloadIdentityPoolProviderOidcArgs( issuer_uri="https://oidc.issuer.com/", allowed_audiences=["my-audience"] )) # IAM role binding to assign the role necessary for LLM. # Replace 'roles/some-gcp-role' with the actual role that grants access to LLM resources. iam_binding = gcp.projects.IAMBinding("my-llm-access-iam-binding", role="roles/some-gcp-role", members=[ pulumi.Output.concat("principalSet://iam.googleapis.com/", workload_identity_pool.name, "/", workload_identity_pool_provider.name) ]) pulumi.export('workload_identity_pool_name', workload_identity_pool.name) pulumi.export('workload_identity_pool_provider_name', workload_identity_pool_provider.name)

    Here's what the program does:

    • It defines a WorkloadIdentityPool, giving it a unique ID and display name. This pool will serve as a container for external identities.
    • A WorkloadIdentityPoolProvider is then established within the pool for OIDC-based identities. You need to replace https://oidc.issuer.com/ with your actual OIDC issuer's URL and specify your intended audience in allowed_audiences.
    • An IAM Binding is created to assign the appropriate role to the identities in the Workload Identity Pool. This role should grant the permissions necessary to access and manage LLMs (e.g., invoking APIs). Make sure to replace roles/some-gcp-role with the specific GCP role required for your LLM resources.

    Each resource is clearly labeled and described with comments. You will need to customize the issuer_uri, allowed_audiences, and the role in the IAM Binding according to your organization's specifics and the needs of your LLMs deployment.

    Remember to replace placeholders like my-llm-workload-pool with the actual identifiers you wish to use for your resources. The pulumi.export lines at the end of the program will output the created resource names once the Pulumi program is deployed. This is useful for debugging and for referencing these resources in other parts of your infrastructure.