1. Policy Management for Secure AI Dataset Access on OCI


    To manage policies for secure AI dataset access on Oracle Cloud Infrastructure (OCI) with Pulumi, you'll need to interact with OCI Identity and Access Management (IAM) services. Policies in OCI are documents that specify who can access which resources and how. They are written in a declarative JSON format and dictate what actions are allowed or denied.

    Pulumi does not have a dedicated OCI provider, but it does provide a way to interact with OCI through the Pulumi Terraform Bridge, which enables you to use Terraform's OCI provider in your Pulumi Python program.

    Here is an example of how you could define and apply an IAM policy for your AI datasets in your OCI environment using Pulumi with the Terraform bridge for OCI. This program assumes you have the proper setup and access to manage OCI resources.

    First, you need to use the pulumi_terraform package to bridge to the OCI Terraform provider.

    import pulumi from pulumi_terraform import TerraformRemoteStateReference # We start by creating a reference to an existing Terraform state that manages OCI resources. # This is necessary because we're going to use Terraform's OCI provider to define an IAM policy. # The Terraform state file must already exist and contain the OCI provider configuration. oci_state = TerraformRemoteStateReference( "oci_state", backend_type="local", args=TerraformRemoteStateReferenceArgs( path="path/to/your/terraform.tfstate" ) ) # Once the state is loaded, you can define resources like you would in a Terraform configuration. # Here we define an OCI IAM policy that allows an AI service to access specific datasets. # Replace the 'compartment_id', 'target_service', and 'dataset_identifier' with the relevant information. policy_document = pulumi.Config("policy_document") ai_dataset_policy = oci_state.get_resource("oci_identity_policy", "ai_dataset_policy", { "name": "AI_Dataset_Access_Policy", "description": "Policy that allows AI services to access specific datasets", "compartment_id": pulumi.Config("compartment_id"), "statements": policy_document.get( "This policy allows service {target_service} to manage objects in buckets {dataset_identifier}" ) }) # We then export the ID of the policy for reference outside of Pulumi. pulumi.export("ai_dataset_policy_id", ai_dataset_policy.id)

    In the above program:

    • We create a TerraformRemoteStateReference to connect to an existing Terraform state. This is where your OCI provider and related configurations should be defined.

    • We use oci_state.get_resource() which interacts with the Terraform State to define an IAM policy (oci_identity_policy). This policy has a name, description, compartment_id, and a set of statements that dictate the access permissions.

    • The policy statements are crafted in a JSON format. For example, it might look something like:

      [ "Allow service {target_service} to manage objects in compartment {compartment_id} where target.bucket.name='{dataset_identifier}'" ]

      Replace {target_service}, {compartment_id}, and {dataset_identifier} with actual values according to your configuration.

    • Lastly, we export the ID of the policy (ai_dataset_policy_id) as an output which can be used to reference the policy elsewhere in your Pulumi program or for other operational purposes.

    Note: This example assumes you have configured access to OCI and Pulumi (through either environment variables or the respective configuration systems) and have an existing Terraform setup managing OCI resources. You will need to replace "path/to/your/terraform.tfstate" with the actual path to your Terraform state file, and populate the policy document and other parameters with values that make sense for your use case.

    Please ensure you have the necessary permissions and have carefully reviewed your policy definitions to avoid granting overly broad access, which could lead to security issues.