1. AI Service Orchestration using Azure API Management

    Python

    Orchestrating AI services with Azure API Management involves setting up various components within the Azure stack to manage, secure, document, and mediate API requests. Azure API Management service is a turnkey solution for publishing APIs to external and internal customers.

    Firstly, we will create an instance of the Azure API Management service. Once it is set up, we can configure the backend services, which will be the AI services we wish to orchestrate. After the backends are added, we can define a product, which is a logical collection of APIs in API Management and is the unit of API access and subscription. We would then create a policy to enforce rules across all API calls, such as setting quotas or transformation of requests/responses.

    Here is a basic Pulumi program to orchestrate an AI service using Azure API Management:

    import pulumi import pulumi_azure_native as azure_native # Provide a name for our API Management service and the resource group it belongs to api_management_service_name = 'my-ai-service-orchestration' resource_group_name = 'my-resource-group' # Create an Azure Resource Group resource_group = azure_native.resources.ResourceGroup('resourceGroup', resource_group_name=resource_group_name) # Create an Azure API Management service instance api_management_service = azure_native.apimanagement.ApiManagementService('apiManagementService', resource_group_name=resource_group.name, service_name=api_management_service_name, publisher_name='Your Publisher Name', publisher_email='your-email@example.com', sku=azure_native.apimanagement.ServiceSkuArgs( capacity=0, name='Consumption', )) # Define backend AI service ai_backend_service = azure_native.apimanagement.Backend('aiBackendService', resource_group_name=resource_group.name, service_name=api_management_service.name, url='https://your-ai-service-endpoint', protocol="http", # Assuming the backend service is over HTTP title='AI Service') # Define a product to logically group your APIs ai_product = azure_native.apimanagement.Product('aiProduct', resource_group_name=resource_group.name, service_name=api_management_service.name, product_name='AI Services', display_name='AI Product', description='A product for AI services', subscription_required=True) # Define a policy to apply to each API global_policy = azure_native.apimanagement.Policy('globalPolicy', resource_group_name=resource_group.name, service_name=api_management_service.name, value='''<policies> <inbound> <base /> <!-- Add more custom policies here --> </inbound> <backend> <base /> </backend> <outbound> <base /> </outbound> <on-error> <base /> </on-error> </policies>''', format="xml") # Policies are defined using XML # Export the API Management service URL pulumi.export('api_management_service_url', api_management_service.gateway_url)

    In this program:

    • We create a resource group to organize all our Azure resources.
    • We then instantiate the API Management service with the required information such as the publisher name and email. We choose the 'Consumption' SKU, which is serverless and meant for lightweight usage patterns.
    • We proceed to define a backend, which represents your AI service. This is the actual service that your API will be forwarding requests to after any policy enforcements or transformations.
    • We also define a product which is a categorization of our AI services and determines how users and applications might subscribe to these APIs.
    • A policy is defined to apply a set of rules across all API calls. In this example, the policy is kept basic, but you could include more advanced settings for caching, transformation, or access control.
    • Finally, we export the URL of the API Management service so that it can be accessed by clients and developers to use the APIs.

    Please replace 'your-ai-service-endpoint' and other placeholder values with actual values of your AI service and contact details. The default policy does not include any specific logic; this would be replaced with any rules you wish to govern your API’s behavior.

    In practice, further steps would involve adding specific APIs to the product, setting up operations, responses, defining more complex policies, and possibly adding a developer portal for API documentation and testing. Each of these components can be managed through separate Pulumi resources, offering a code-driven approach to API management.


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