azure-mgmt-apimanagement-py

작성자: microsoft

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

🔑 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 — 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.

microsoft의 다른 스킬

oss-growth
microsoft
OSS 성장 해커 페르소나
agent-framework-azure-ai-py
microsoft
Microsoft Agent Framework Python SDK(agent-framework-azure-ai)를 사용하여 Azure AI Foundry 에이전트를 구축합니다. AzureAIAgentsProvider로 지속적 에이전트를 만들 때, 호스팅 도구(코드 인터프리터, 파일 검색, 웹 검색)를 사용할 때, MCP 서버를 통합할 때, 대화 스레드를 관리할 때, 또는 스트리밍 응답을 구현할 때 사용합니다. 함수 도구, 구조화된 출력, 다중 도구 에이전트를 다룹니다.
development
airunway-aks-setup
microsoft
Set up AI Runway on AKS — 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
Azure Application Insights로 웹앱을 계측하기 위한 지침입니다. 원격 분석 패턴, SDK 설정, 구성 참조를 제공합니다. WHEN: 앱 계측 방법, App Insights SDK, 원격 분석 패턴, App Insights란 무엇인가, Application Insights 지침, 계측 예시, APM 모범 사례.
devops
applicationinsights-web-ts
microsoft
브라우저/웹 앱을 Application Insights JavaScript SDK(@microsoft/applicationinsights-web)로 계측합니다. Real User Monitoring(RUM) — 페이지 뷰, 클릭, AJAX/fetch 종속성, 예외, 사용자 지정 이벤트, 백엔드 OpenTelemetry 트레이스와 상관관계가 있는 브라우저 측 GenAI 에이전트 트레이스에 사용합니다. SDK Loader Script 및 npm 설정, 프레임워크 확장(React, React Native, Angular), Click Analytics, 텔레메트리 이니셜라이저, 브라우저에서 생성된 에이전트/도구/모델 스팬에 대한 OTel GenAI 의미론적 규칙을 다룹니다.
devops
azure-ai-anomalydetector-java
microsoft
Azure AI Anomaly Detector SDK for Java로 이상 탐지 애플리케이션을 구축하세요. 단변량/다변량 이상 탐지, 시계열 분석 또는 AI 기반 모니터링을 구현할 때 사용하세요.
development
azure-ai-language-conversations-py
microsoft
azure-ai-language-conversations Python SDK를 사용하여 대화형 언어 이해(CLU)를 구현합니다. ConversationAnalysisClient로 대화 의도와 엔터티를 분석하거나, NLP 기능을 구축하거나, 애플리케이션에 언어 이해를 통합할 때 사용합니다.
development
azure-ai-ml-py
microsoft
Azure Machine Learning SDK v2 for Python. ML 작업 영역, 작업, 모델, 데이터 세트, 컴퓨팅 및 파이프라인에 사용합니다. 트리거: "azure-ai-ml", "MLClient", "workspace", "model registry", "training jobs", "datasets".
development