azure-mgmt-apimanagement-py

Azure API Management SDK for Python. Use for managing APIM services, APIs, products, subscriptions, and policies. Triggers: "azure-mgmt-apimanagement", "ApiManagementClient", "APIM", "API gateway", "API Management".

npx skills add https://github.com/microsoft/skills --skill azure-mgmt-apimanagement-py

Azure API Management SDK for Python

Manage Azure API Management services, APIs, products, and policies.

Installation

pip install azure-mgmt-apimanagement
pip install azure-identity

Environment Variables

AZURE_SUBSCRIPTION_ID=your-subscription-id  # Required for all auth methods
AZURE_TOKEN_CREDENTIALS=prod # Required only if DefaultAzureCredential is used in production

Authentication & Lifecycle

πŸ”‘ Two rules apply to every code sample below:

  1. Prefer DefaultAzureCredential. It works locally (Azure CLI / VS Code / Developer CLI) and in Azure (managed identity, workload identity) with no code change. Avoid connection strings, account/API keys β€” they bypass Entra audit and rotation.
    • Local dev: DefaultAzureCredential works as-is.
    • Production: set AZURE_TOKEN_CREDENTIALS=prod (or AZURE_TOKEN_CREDENTIALS=<specific_credential>) to constrain the credential chain to production-safe credentials.
  2. Wrap every client in a context manager so HTTP transports, sockets, and token caches are released deterministically:
    • Sync: with <Client>(...) as client:
    • Async: async with <Client>(...) as client: and async with DefaultAzureCredential() as credential: (from azure.identity.aio)

Snippets may abbreviate this setup, but production code should always follow both rules.

from azure.identity import DefaultAzureCredential
from azure.mgmt.apimanagement import ApiManagementClient
import os

with ApiManagementClient(
    credential=DefaultAzureCredential(),
    subscription_id=os.environ["AZURE_SUBSCRIPTION_ID"]
) as client:
    # Use `client` for all subsequent operations (see examples below)
    ...

Create APIM Service

from azure.mgmt.apimanagement.models import (
    ApiManagementServiceResource,
    ApiManagementServiceSkuProperties,
    SkuType
)

service = client.api_management_service.begin_create_or_update(
    resource_group_name="my-resource-group",
    service_name="my-apim",
    parameters=ApiManagementServiceResource(
        location="eastus",
        publisher_email="admin@example.com",
        publisher_name="My Organization",
        sku=ApiManagementServiceSkuProperties(
            name=SkuType.DEVELOPER,
            capacity=1
        )
    )
).result()

print(f"Created APIM: {service.name}")

Import API from OpenAPI

from azure.mgmt.apimanagement.models import (
    ApiCreateOrUpdateParameter,
    ContentFormat,
    Protocol
)

api = client.api.begin_create_or_update(
    resource_group_name="my-resource-group",
    service_name="my-apim",
    api_id="my-api",
    parameters=ApiCreateOrUpdateParameter(
        display_name="My API",
        path="myapi",
        protocols=[Protocol.HTTPS],
        format=ContentFormat.OPENAPI_JSON,
        value='{"openapi": "3.0.0", "info": {"title": "My API", "version": "1.0"}, "paths": {"/health": {"get": {"responses": {"200": {"description": "OK"}}}}}}'
    )
).result()

print(f"Imported API: {api.display_name}")

Import API from URL

api = client.api.begin_create_or_update(
    resource_group_name="my-resource-group",
    service_name="my-apim",
    api_id="petstore",
    parameters=ApiCreateOrUpdateParameter(
        display_name="Petstore API",
        path="petstore",
        protocols=[Protocol.HTTPS],
        format=ContentFormat.OPENAPI_LINK,
        value="https://petstore.swagger.io/v2/swagger.json"
    )
).result()

List APIs

apis = client.api.list_by_service(
    resource_group_name="my-resource-group",
    service_name="my-apim"
)

for api in apis:
    print(f"{api.name}: {api.display_name} - {api.path}")

Create Product

from azure.mgmt.apimanagement.models import ProductContract

product = client.product.create_or_update(
    resource_group_name="my-resource-group",
    service_name="my-apim",
    product_id="premium",
    parameters=ProductContract(
        display_name="Premium",
        description="Premium tier with unlimited access",
        subscription_required=True,
        approval_required=False,
        state="published"
    )
)

print(f"Created product: {product.display_name}")

Add API to Product

client.product_api.create_or_update(
    resource_group_name="my-resource-group",
    service_name="my-apim",
    product_id="premium",
    api_id="my-api"
)

Create Subscription

from azure.mgmt.apimanagement.models import SubscriptionCreateParameters

subscription = client.subscription.create_or_update(
    resource_group_name="my-resource-group",
    service_name="my-apim",
    sid="my-subscription",
    parameters=SubscriptionCreateParameters(
        display_name="My Subscription",
        scope=f"/products/premium",
        state="active"
    )
)

print(f"Subscription key: {subscription.primary_key}")

Set API Policy

from azure.mgmt.apimanagement.models import PolicyContract

policy_xml = """
<policies>
    <inbound>
        <rate-limit calls="100" renewal-period="60" />
        <set-header name="X-Custom-Header" exists-action="override">
            <value>CustomValue</value>
        </set-header>
    </inbound>
    <backend>
        <forward-request />
    </backend>
    <outbound />
    <on-error />
</policies>
"""

client.api_policy.create_or_update(
    resource_group_name="my-resource-group",
    service_name="my-apim",
    api_id="my-api",
    policy_id="policy",
    parameters=PolicyContract(
        value=policy_xml,
        format="xml"
    )
)

Create Named Value (Secret)

from azure.mgmt.apimanagement.models import NamedValueCreateContract

named_value = client.named_value.begin_create_or_update(
    resource_group_name="my-resource-group",
    service_name="my-apim",
    named_value_id="backend-api-key",
    parameters=NamedValueCreateContract(
        display_name="Backend API Key",
        value="secret-key-value",
        secret=True
    )
).result()

Create Backend

from azure.mgmt.apimanagement.models import BackendContract

backend = client.backend.create_or_update(
    resource_group_name="my-resource-group",
    service_name="my-apim",
    backend_id="my-backend",
    parameters=BackendContract(
        url="https://api.backend.example.com",
        protocol="http",
        description="My backend service"
    )
)

Create User

from azure.mgmt.apimanagement.models import UserCreateParameters

user = client.user.create_or_update(
    resource_group_name="my-resource-group",
    service_name="my-apim",
    user_id="newuser",
    parameters=UserCreateParameters(
        email="user@example.com",
        first_name="John",
        last_name="Doe"
    )
)

Operation Groups

GroupPurpose
api_management_serviceAPIM instance management
apiAPI operations
api_operationAPI operation details
api_policyAPI-level policies
productProduct management
product_apiProduct-API associations
subscriptionSubscription management
userUser management
named_valueNamed values/secrets
backendBackend services
certificateCertificates
gatewaySelf-hosted gateways

Best Practices

  1. Pick sync OR async and stay consistent. Do not mix azure.xxx sync clients with azure.xxx.aio async clients in the same call path. Choose one mode per module.
  2. Always use context managers for clients and async credentials. Wrap every client in with Client(...) as client: (sync) or async with Client(...) as client: (async). For async DefaultAzureCredential from azure.identity.aio, also use async with credential: so tokens and transports are cleaned up.
  3. Use named values for secrets and configuration
  4. Apply policies at appropriate scopes (global, product, API, operation)
  5. Use products to bundle APIs and manage access
  6. Enable Application Insights for monitoring
  7. Use backends to abstract backend services
  8. Version your APIs using APIM's versioning features

Reference Files

FileContents
references/capabilities.mdAdditional non-hero capabilities, operation-group coverage, and production checklists.
references/non-hero-scenarios.mdDedicated non-hero examples for secondary/advanced scenarios.

More skills from microsoft

oss-growth
microsoft
OSS growth hacker persona
agent-framework-azure-ai-py
microsoft
Build Azure AI Foundry agents using the Microsoft Agent Framework Python SDK (agent-framework-azure-ai). Use when creating persistent agents with AzureAIAgentsProvider, using hosted tools (code interpreter, file search, web search), integrating MCP servers, managing conversation threads, or implementing streaming responses. Covers function tools, structured outputs, and multi-tool agents.
development
airunway-aks-setup
microsoft
Set up AI Runway on AKS β€” from bare cluster to running model. Covers cluster verification, controller install, GPU assessment, provider setup, and first deployment. WHEN: "setup AI Runway", "onboard AKS cluster", "install AI Runway", "airunway setup", "deploy model to AKS", "GPU inference on AKS", "KAITO setup on AKS", "run LLM on AKS", "vLLM on AKS", "set up model serving on AKS", "AI Runway controller".
devops
appinsights-instrumentation
microsoft
Guidance for instrumenting webapps with Azure Application Insights. Provides telemetry patterns, SDK setup, and configuration references. WHEN: how to instrument app, App Insights SDK, telemetry patterns, what is App Insights, Application Insights guidance, instrumentation examples, APM best practices.
devops
applicationinsights-web-ts
microsoft
Instrument browser/web apps with the Application Insights JavaScript SDK (@microsoft/applicationinsights-web). Use for Real User Monitoring (RUM) β€” page views, clicks, AJAX/fetch dependencies, exceptions, custom events, and browser-side GenAI agent traces correlated to backend OpenTelemetry traces. Covers SDK Loader Script and npm setup, framework extensions (React, React Native, Angular), Click Analytics, telemetry initializers, and OTel GenAI semantic conventions for agent/tool/model spans emitted from the browser.
devops
azure-ai-anomalydetector-java
microsoft
Build anomaly detection applications with Azure AI Anomaly Detector SDK for Java. Use when implementing univariate/multivariate anomaly detection, time-series analysis, or AI-powered monitoring.
development
azure-ai-language-conversations-py
microsoft
Implement Conversational Language Understanding (CLU) using the azure-ai-language-conversations Python SDK. Use when working with ConversationAnalysisClient to analyze conversation intent and entities, building NLP features, or integrating language understanding into applications.
development
azure-ai-ml-py
microsoft
Azure Machine Learning SDK v2 for Python. Use for ML workspaces, jobs, models, datasets, compute, and pipelines. Triggers: "azure-ai-ml", "MLClient", "workspace", "model registry", "training jobs", "datasets".
development