1. Global Content Distribution for AI Service APIs with Azure Front Door


    To set up global content distribution for AI service APIs with Azure Front Door, you would typically need to:

    1. Define your AI Service's endpoints, ensuring that they are globally distributed for high availability and load distribution. You'll place these endpoints behind Azure Front Door to take advantage of its routing and acceleration features.
    2. Define a Front Door resource, defining its routing rules and backend pools that point to your service APIs.
    3. Apply security rules, such as WAF (Web Application Firewall) policies, to protect your service.

    Here's how you would achieve this using Pulumi and the Azure Native resource provider.

    First, you need to create a resource group where all your resources will reside. Next, you'll create an instance of Azure Front Door, configure its frontend endpoints, backend pools, and routing rules. Backend pools will point to the regions where your service's instances are hosted, and routing rules will define how traffic is forwarded to these backends.

    Additionally, you may want to set up a health probe to automatically check the health of your service endpoints and a WAF policy to protect your APIs from common threats.

    Let's translate this into a Pulumi program in Python:

    import pulumi import pulumi_azure_native as azure_native # Step 1: Create a Resource Group resource_group = azure_native.resources.ResourceGroup("resourceGroup") # Step 2: Create a Front Door profile front_door_profile = azure_native.cdn.FrontDoor("frontDoorProfile", resource_group_name=resource_group.name, tags={ "Environment": "Production", } ) # Step 3: Define Backend Pools for your service APIs backend_pool = azure_native.cdn.BackendPool("backendPool", resource_group_name=resource_group.name, frontend_endpoint_ids=[ # The ID of the frontend endpoint will be added here pulumi.Output.concat("/subscriptions/", pulumi.get_project(), "/resourceGroups/", resource_group.name, "/providers/Microsoft.Network/frontdoors/frontDoorProfile/frontendEndpoints/myFrontDoorFrontendEndpoint"), ], backends=[ # You need to define at least one backend - your API service hosted in Azure, for example an Azure App Service azure_native.cdn.BackendArgs( address="myapiservice.azurewebsites.net", http_port=80, https_port=443, weight=50, priority=1, enabled_state="Enabled", ), ], load_balancing_settings=azure_native.cdn.LoadBalancingSettingsModelArgs( sample_size=4, successful_samples_required=2, ), health_probe_settings=azure_native.cdn.HealthProbeSettingsModelArgs( probe_path="/health", protocol="Https", probe_method="GET", ), ) # Step 4: Define a Routing Rule routing_rule = azure_native.cdn.RoutingRule("routingRule", resource_group_name=resource_group.name, frontend_endpoint_ids=[ # The ID of the frontend endpoint will be added here pulumi.Output.concat("/subscriptions/", pulumi.get_project(), "/resourceGroups/", resource_group.name, "/providers/Microsoft.Network/frontdoors/frontDoorProfile/frontendEndpoints/myFrontDoorFrontendEndpoint"), ], accepted_protocols=["Https"], patterns_to_match=["/*"], route_configuration=azure_native.cdn.ForwardingConfigurationArgs( forwarding_protocol="HttpsOnly", backend_pool_id=backend_pool.id, ), enabled_state="Enabled", ) # Step 5: Enable WAF waf_policy = azure_native.cdn.WebApplicationFirewallPolicy("wafPolicy", resource_group_name=resource_group.name, custom_rules=[ # You may define custom rules specific to your application's needs azure_native.cdn.CustomRuleArgs( name="BlockBadRequests", action="Block", rule_type="MatchRule", priority=1, match_conditions=[ azure_native.cdn.MatchConditionArgs( match_value=["BadBot"], operator="Contains", match_variable="RequestHeaderNames", ), ], ), ], policy_settings=azure_native.cdn.PolicySettingsArgs( default_custom_block_response_status_code=403, default_custom_block_response_body="Blocked by WAF", ), ) # Output the Front Door endpoint URL pulumi.export("frontDoorEndpoint", front_door_profile.frontend_endpoints[0].host_name)

    In the above code:

    • We create a resource group that will contain all our Azure resources.
    • We instantiate an Azure Front Door profile, specifying the name and tagging it with an environment name.
    • We define a backend pool that points to the backend hosting our service. This example just includes one backend, which would be your AI service hosted on Azure.
    • We add a routing rule to forward HTTP(s) traffic from the frontend to the backend pool we defined. The pattern /* means that all routes are matched.
    • We add a WAF policy to help secure our service API against common threats. You may need to adjust your custom rules and the WAF policy settings based on your actual security requirements.
    • Finally, we export the hostname of the Front Door frontend endpoint so that it can be used or referenced externally.

    Please note this is a general setup. Depending on your application and its architecture, you might need to adjust backend pool properties, health probe paths, load-balancing settings, and WAF rules. The components can be expanded to include additional features like custom domains, SSL certification, compression settings, etc.