azure-mgmt-apicenter-py – skill DevOps & Hạ tầng cho agent AI

Azure API Center Management SDK for Python

Manage API inventory, metadata, and governance in Azure API Center.

Installation

pip install azure-mgmt-apicenter
pip install azure-identity

Environment Variables

AZURE_SUBSCRIPTION_ID=your-subscription-id

Authentication

from azure.identity import DefaultAzureCredential
from azure.mgmt.apicenter import ApiCenterMgmtClient
import os

client = ApiCenterMgmtClient(
    credential=DefaultAzureCredential(),
    subscription_id=os.environ["AZURE_SUBSCRIPTION_ID"]
)

Create API Center

from azure.mgmt.apicenter.models import Service

api_center = client.services.create_or_update(
    resource_group_name="my-resource-group",
    service_name="my-api-center",
    resource=Service(
        location="eastus",
        tags={"environment": "production"}
    )
)

print(f"Created API Center: {api_center.name}")

List API Centers

api_centers = client.services.list_by_subscription()

for api_center in api_centers:
    print(f"{api_center.name} - {api_center.location}")

Register an API

from azure.mgmt.apicenter.models import Api, ApiKind, LifecycleStage

api = client.apis.create_or_update(
    resource_group_name="my-resource-group",
    service_name="my-api-center",
    workspace_name="default",
    api_name="my-api",
    resource=Api(
        title="My API",
        description="A sample API for demonstration",
        kind=ApiKind.REST,
        lifecycle_stage=LifecycleStage.PRODUCTION,
        terms_of_service={"url": "https://example.com/terms"},
        contacts=[{"name": "API Team", "email": "[email protected]"}]
    )
)

print(f"Registered API: {api.title}")

Create API Version

from azure.mgmt.apicenter.models import ApiVersion, LifecycleStage

version = client.api_versions.create_or_update(
    resource_group_name="my-resource-group",
    service_name="my-api-center",
    workspace_name="default",
    api_name="my-api",
    version_name="v1",
    resource=ApiVersion(
        title="Version 1.0",
        lifecycle_stage=LifecycleStage.PRODUCTION
    )
)

print(f"Created version: {version.title}")

Add API Definition

from azure.mgmt.apicenter.models import ApiDefinition

definition = client.api_definitions.create_or_update(
    resource_group_name="my-resource-group",
    service_name="my-api-center",
    workspace_name="default",
    api_name="my-api",
    version_name="v1",
    definition_name="openapi",
    resource=ApiDefinition(
        title="OpenAPI Definition",
        description="OpenAPI 3.0 specification"
    )
)

Import API Specification

from azure.mgmt.apicenter.models import ApiSpecImportRequest, ApiSpecImportSourceFormat

# Import from inline content
client.api_definitions.import_specification(
    resource_group_name="my-resource-group",
    service_name="my-api-center",
    workspace_name="default",
    api_name="my-api",
    version_name="v1",
    definition_name="openapi",
    body=ApiSpecImportRequest(
        format=ApiSpecImportSourceFormat.INLINE,
        value='{"openapi": "3.0.0", "info": {"title": "My API", "version": "1.0"}, "paths": {}}'
    )
)

List APIs

apis = client.apis.list(
    resource_group_name="my-resource-group",
    service_name="my-api-center",
    workspace_name="default"
)

for api in apis:
    print(f"{api.name}: {api.title} ({api.kind})")

Create Environment

from azure.mgmt.apicenter.models import Environment, EnvironmentKind

environment = client.environments.create_or_update(
    resource_group_name="my-resource-group",
    service_name="my-api-center",
    workspace_name="default",
    environment_name="production",
    resource=Environment(
        title="Production",
        description="Production environment",
        kind=EnvironmentKind.PRODUCTION,
        server={"type": "Azure API Management", "management_portal_uri": ["https://portal.azure.com"]}
    )
)

Create Deployment

from azure.mgmt.apicenter.models import Deployment, DeploymentState

deployment = client.deployments.create_or_update(
    resource_group_name="my-resource-group",
    service_name="my-api-center",
    workspace_name="default",
    api_name="my-api",
    deployment_name="prod-deployment",
    resource=Deployment(
        title="Production Deployment",
        description="Deployed to production APIM",
        environment_id="/workspaces/default/environments/production",
        definition_id="/workspaces/default/apis/my-api/versions/v1/definitions/openapi",
        state=DeploymentState.ACTIVE,
        server={"runtime_uri": ["https://api.example.com"]}
    )
)

Define Custom Metadata

from azure.mgmt.apicenter.models import MetadataSchema

metadata = client.metadata_schemas.create_or_update(
    resource_group_name="my-resource-group",
    service_name="my-api-center",
    metadata_schema_name="data-classification",
    resource=MetadataSchema(
        schema='{"type": "string", "title": "Data Classification", "enum": ["public", "internal", "confidential"]}'
    )
)

Client Types

| Client | Purpose |

|--------|---------|

| ApiCenterMgmtClient | Main client for all operations |

Operations

| Operation Group | Purpose |

|----------------|---------|

| services | API Center service management |

| workspaces | Workspace management |

| apis | API registration and management |

| api_versions | API version management |

| api_definitions | API definition management |

| deployments | Deployment tracking |

| environments | Environment management |

| metadata_schemas | Custom metadata definitions |

Best Practices

1. Use workspaces to organize APIs by team or domain

2. Define metadata schemas for consistent governance

3. Track deployments to understand where APIs are running

4. Import specifications to enable API analysis and linting

5. Use lifecycle stages to track API maturity

6. Add contacts for API ownership and support

When to Use

This skill is applicable to execute the workflow or actions described in the overview.

Limitations

• Use this skill only when the task clearly matches the scope described above.
• Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
• Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.