Securing Access to Azure Cognitive Services with Policy Assignments

Question

Pulumi · Accepted Answer

To secure access to Azure Cognitive Services using policy assignments, we will use Pulumi's infrastructure as code (IaC) approach. Specifically, we'll utilize the `azure-native.authorization.PolicyAssignment` resource from the Pulumi Azure Native provider. This allows us to apply a policy that could enforce certain rules or actions like restricting access to authorized networks or ensuring certain compliance standards.

Here are the steps we will take in our Pulumi program:
1. Define a policy definition that includes rules for allowed actions or restricted settings.
2. Create a policy assignment that assigns the policy definition to our Azure Cognitive Services account.
3. Optionally, customize the policy assignment by setting parameters such as the scope, enforcement mode, or non-compliance messages.

Now, let's create a Pulumi program in Python that demonstrates how to secure access to Azure Cognitive Services with policy assignments.

```python
import pulumi
import pulumi_azure_native as azure_native

# Step 1: Define a policy definition that specifies the rules for securing access.
# In this example, we'd create a policy for allowed IP ranges to access the Cognitive Services.
# However, the specific details of the policy rule depend on the organization's security requirements.

# Define the policy rule (in this example, an allowed IP range for simplicity).
# You should adjust this JSON to implement the actual security policy you need.
allowed_ip_range_policy_rule = {
    "if": {
        # Replace '...' with the actual condition for the allowed IP ranges
        # The details of this condition will be specific to your Azure environment and security requirements
    },
    "then": {
        "effect": "deny"
    }
}

# Create a policy definition with the defined rule.
policy_definition = azure_native.authorization.PolicyDefinition(
    "cognitiveServicesAllowedIPRangePolicy",
    policy_rule=allowed_ip_range_policy_rule,
    policy_type="Custom"
)

# Step 2: Assign the policy to the Cognitive Services account.

# Policy Assignment parameters
policy_assignment_params = azure_native.authorization.PolicyAssignmentArgs(
    scope=..., # Replace with the scope identifier for your Azure Cognitive Services account
    policy_definition_id=policy_definition.id, # Reference the policy definition created earlier
    enforcement_mode="Default" # Can be "Default" or "DoNotEnforce"
)

# Create the policy assignment
policy_assignment = azure_native.authorization.PolicyAssignment(
    "cognitiveServicesPolicyAssignment",
    args=policy_assignment_params
)

# Pulumi always requires at least one export but we do not have any meaningful output in this example.
# However, we can export the policy assignment ID to show the assignment was successful.
pulumi.export('policy_assignment_id', policy_assignment.id)
```

This program demonstrates the basic use of policy definitions and assignments in Pulumi to manage access to Azure resources in this case, Cognitive Services. You would replace the placeholder '...' with actual conditions, scope, and other necessary configurations matching your organization's security requirements.

The `scope` parameter of the policy assignment specifies the Cognitive Services account to which the policy should be applied. The `policy_definition_id` refers to the policy rule we defined earlier. The `enforcement_mode` determines whether the policy will be enforced or just audited.

Once you've adjusted the policy rule and other parameters to fit your security requirements, you would run this Pulumi program using the Pulumi CLI. After successfully running it, your Azure Cognitive Services account will be secured according to the policies you've defined.