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

🔑 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.

Plus de skills de microsoft

oss-growth
microsoft
Persona de growth hacker OSS
agent-framework-azure-ai-py
microsoft
Créez des agents Azure AI Foundry à l’aide du SDK Python Microsoft Agent Framework (agent-framework-azure-ai). À utiliser lors de la création d’agents persistants avec AzureAIAgentsProvider, de l’utilisation d’outils hébergés (interpréteur de code, recherche de fichiers, recherche web), de l’intégration de serveurs MCP, de la gestion de fils de conversation ou de l’implémentation de réponses en streaming. Couvre les outils de fonction, les sorties structurées et les agents multi-outils.
development
airunway-aks-setup
microsoft
Configurez AI Runway sur AKS — du cluster nu au modèle en cours d'exécution. Couvre la vérification du cluster, l'installation du contrôleur, l'évaluation GPU, la configuration du fournisseur et le premier déploiement. QUAND : « configurer AI Runway », « intégrer un cluster AKS », « installer AI Runway », « configuration airunway », « déployer un modèle sur AKS », « inférence GPU sur AKS », « configuration KAITO sur AKS », « exécuter LLM sur AKS », « vLLM sur AKS », « configurer le service de modèles sur AKS », « contrôleur AI Runway ».
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
Instrumentez les applications navigateur/web avec le SDK JavaScript Application Insights (@microsoft/applicationinsights-web). Utilisez-le pour la surveillance des utilisateurs réels (RUM) — vues de page, clics, dépendances AJAX/fetch, exceptions, événements personnalisés et traces d’agents GenAI côté navigateur corrélées aux traces OpenTelemetry backend. Couvre le script de chargement du SDK et la configuration npm, les extensions de framework (React, React Native, Angular), Click Analytics, les initialiseurs de télémétrie et les conventions sémantiques OTel GenAI pour les spans d’agents/outils/modèles émises depuis le navigateur.
devops
azure-ai-anomalydetector-java
microsoft
Créez des applications de détection d'anomalies avec le SDK Azure AI Anomaly Detector pour Java. Utilisez-le lors de l'implémentation de la détection d'anomalies univariées/multivariées, de l'analyse de séries temporelles ou de la surveillance basée sur l'IA.
development
azure-ai-language-conversations-py
microsoft
Implémentez la compréhension du langage conversationnel (CLU) à l’aide du SDK Python azure-ai-language-conversations. Utilisez-le lorsque vous travaillez avec ConversationAnalysisClient pour analyser l’intention et les entités d’une conversation, créer des fonctionnalités de NLP ou intégrer la compréhension du langage dans des applications.
development
azure-ai-ml-py
microsoft
SDK v2 d’Azure Machine Learning pour Python. Utiliser pour les espaces de travail ML, les tâches, les modèles, les jeux de données, le calcul et les pipelines. Déclencheurs : « azure-ai-ml », « MLClient », « espace de travail », « registre de modèles », « tâches d’entraînement », « jeux de données ».
development