Secure Model Registry on OpenShift Integrated Registry

Question

Pulumi · Accepted Answer

To deploy a secure model registry using OpenShift's integrated registry, we'll create a project using Pulumi to provision the necessary infrastructure, including an OpenShift cluster and supporting resources required for a model registry. The integrated registry in OpenShift will serve as a private Docker registry, where you can push and pull your machine learning models packaged as Docker images.

Here's a high-level overview of the process:

1. Set up an Azure Red Hat OpenShift cluster.
2. Configure the integrated OpenShift registry to store model images.
3. Ensure that the registry is secure by following best practices, typically including role-based access control, authentication, and logging.
4. (Optional) Some model registries might require additional components such as a front-end UI or metadata store, which can be layered on top of the cluster as well.

Let's start by creating a Red Hat OpenShift cluster on Azure. We will then set up the integrated registry that comes with OpenShift. We ensure the registry is secure by using standard OpenShift security measures, including proper role-based access control (RBAC) configurations.

### Pulumi Program to Create a Secure Model Registry

Below is a Pulumi program written in Python that provisions an Azure Red Hat OpenShift cluster. Please note that due to the complexity of a managed OpenShift service, some configurations like network profiles, service principal credentials, and others are necessary but are simplified in the code for the sake of this example.

This program assumes you have already logged into the Azure CLI and set up the Pulumi CLI with the necessary credentials.

```python
import pulumi
import pulumi_azure_native as azure_native

# Configuration variables for the cluster.
# Replace these with your specific details where necessary.
RESOURCE_GROUP_NAME = "MyResourceGroup"
CLUSTER_NAME = "MyOpenShiftCluster"
LOCATION = "East US"  # Replace with the location you prefer.
NODE_COUNT = 3  # The number of worker nodes for your OpenShift cluster.

# Create a new resource group if it doesn't exist.
resource_group = azure_native.resources.ResourceGroup(
    "resource_group",
    resource_group_name=RESOURCE_GROUP_NAME,
    location=LOCATION,
)

# Create an Azure Red Hat OpenShift cluster.
openshift_cluster = azure_native.redhatopenshift.OpenShiftCluster(
    "openshift_cluster",
    resource_name=CLUSTER_NAME,
    resource_group_name=resource_group.name,
    location=resource_group.location,
    cluster_profile=azure_native.redhatopenshift.OpenShiftClusterClusterProfileArgs(
        resource_group_id=resource_group.id,
        domain="mydomain",  # Replace with your domain name.
        version="4.3.0",  # Replace with the version you require.
        pull_secret="{}"  # Your pull secret to authenticate with Red Hat.
    ),
    master_profile=azure_native.redhatopenshift.OpenShiftClusterMasterProfileArgs(
        vm_size="Standard_D8s_v3",  # Select the appropriate VM size for your use case.
    ),
    worker_profiles=[azure_native.redhatopenshift.OpenShiftClusterWorkerProfileArgs(
        name="worker",
        vm_size="Standard_D4s_v3",  # Select the appropriate VM size for your use case.
        disk_size_gb=128,
        subnet_id="subnetid",  # Replace with the subnet ID of your VNet.
        count=NODE_COUNT,
    )],
    service_principal_profile=azure_native.redhatopenshift.OpenShiftClusterServicePrincipalProfileArgs(
        client_id="clientId",  # Replace with your service principal's client ID.
        client_secret="secret",  # Replace with your service principal's secret.
    ),
)

# Configure RBAC for the OpenShift integrated registry.
# In a real-world scenario, you may need to specify finer grained permissions.
# This typically involves setting up role bindings for your users to access the registry namespace.
# Due to the complexity, this example does not include explicit RBAC configurations.

# Finally, export the OpenShift cluster credentials so you can access your cluster.
cluster_admin_credentials = pulumi.Output.all(openshift_cluster.name, resource_group.name).apply(
    lambda args: azure_native.redhatopenshift.listOpenShiftClusterAdminCredentials(
        resource_name=args[0],
        resource_group_name=args[1],
    )
)

pulumi.export("kubeconfig", cluster_admin_credentials.kubeconfig)
pulumi.export("cluster_name", openshift_cluster.name)
```

This program performs the following actions:
- It creates a new Azure resource group if it does not already exist.
- It provisions a new Azure Red Hat OpenShift cluster within the specified resource group.
- It configures the service principal credentials, which are required for the OpenShift cluster to interact with Azure APIs.
- It sets up the worker nodes according to the specified node count and VM size.
- Finally, it exports the cluster name and kubeconfig, which can be used to interact with the cluster using `kubectl` or the OpenShift CLI (`oc`).

After setting up the cluster, you can configure the OpenShift integrated registry by applying the appropriate image registry operator and access policies. This typically includes setting the registry to accept pushes of images and configuring storage.

For actual deployments, you will need to refine this code further, for instance, by providing a real domain name, pull secret, subnet ID, and finer-grained RBAC configurations. Remember, managing access control through RBAC is a key aspect of securing your model registry.