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azure-mgmt-fabric-py

Azure Fabric Management SDK for Python. Use for managing Microsoft Fabric capacities and resources. Triggers: "azure-mgmt-fabric", "FabricMgmtClient", "Fabric capacity", "Microsoft Fabric", "Power BI capacity".

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  • SKILL.md8.7 KB
  • references/capabilities.md2.5 KB
  • references/non-hero-scenarios.md3.3 KB

SKILL.md(原文)

インストールする前に、エージェントに与えられる指示の中身を確認できます。

Azure Fabric Management SDK for Python

Manage Microsoft Fabric capacities and resources programmatically.

Installation

pip install azure-mgmt-fabric
pip install azure-identity

Environment Variables

AZURE_SUBSCRIPTION_ID=<your-subscription-id>  # Required for all auth methods
AZURE_RESOURCE_GROUP=<your-resource-group>  # 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, ManagedIdentityCredential
from azure.mgmt.fabric import FabricMgmtClient
import os

# Local dev: DefaultAzureCredential. Production: set AZURE_TOKEN_CREDENTIALS=prod or AZURE_TOKEN_CREDENTIALS=<specific_credential>
credential = DefaultAzureCredential(require_envvar=True)
# Or use a specific credential directly in production:
# See https://learn.microsoft.com/python/api/overview/azure/identity-readme?view=azure-python#credential-classes
# credential = ManagedIdentityCredential()

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

Create Fabric Capacity

from azure.mgmt.fabric import FabricMgmtClient
from azure.mgmt.fabric.models import FabricCapacity, FabricCapacityProperties, CapacitySku
from azure.identity import DefaultAzureCredential
import os

resource_group = os.environ["AZURE_RESOURCE_GROUP"]
capacity_name = "myfabriccapacity"

credential = DefaultAzureCredential()
with FabricMgmtClient(
    credential=credential,
    subscription_id=os.environ["AZURE_SUBSCRIPTION_ID"]
) as client:
    capacity = client.fabric_capacities.begin_create_or_update(
        resource_group_name=resource_group,
        capacity_name=capacity_name,
        resource=FabricCapacity(
            location="eastus",
            sku=CapacitySku(
                name="F2",  # Fabric SKU
                tier="Fabric"
            ),
            properties=FabricCapacityProperties(
                administration=FabricCapacityAdministration(
                    members=["user@contoso.com"]
                )
            )
        )
    ).result()

print(f"Capacity created: {capacity.name}")

Get Capacity Details

capacity = client.fabric_capacities.get(
    resource_group_name=resource_group,
    capacity_name=capacity_name
)

print(f"Capacity: {capacity.name}")
print(f"SKU: {capacity.sku.name}")
print(f"State: {capacity.properties.state}")
print(f"Location: {capacity.location}")

List Capacities in Resource Group

capacities = client.fabric_capacities.list_by_resource_group(
    resource_group_name=resource_group
)

for capacity in capacities:
    print(f"Capacity: {capacity.name} - SKU: {capacity.sku.name}")

List All Capacities in Subscription

all_capacities = client.fabric_capacities.list_by_subscription()

for capacity in all_capacities:
    print(f"Capacity: {capacity.name} in {capacity.location}")

Update Capacity

from azure.mgmt.fabric.models import FabricCapacityUpdate, CapacitySku

updated = client.fabric_capacities.begin_update(
    resource_group_name=resource_group,
    capacity_name=capacity_name,
    properties=FabricCapacityUpdate(
        sku=CapacitySku(
            name="F4",  # Scale up
            tier="Fabric"
        ),
        tags={"environment": "production"}
    )
).result()

print(f"Updated SKU: {updated.sku.name}")

Suspend Capacity

Pause capacity to stop billing:

client.fabric_capacities.begin_suspend(
    resource_group_name=resource_group,
    capacity_name=capacity_name
).result()

print("Capacity suspended")

Resume Capacity

Resume a paused capacity:

client.fabric_capacities.begin_resume(
    resource_group_name=resource_group,
    capacity_name=capacity_name
).result()

print("Capacity resumed")

Delete Capacity

client.fabric_capacities.begin_delete(
    resource_group_name=resource_group,
    capacity_name=capacity_name
).result()

print("Capacity deleted")

Check Name Availability

from azure.mgmt.fabric.models import CheckNameAvailabilityRequest

result = client.fabric_capacities.check_name_availability(
    location="eastus",
    body=CheckNameAvailabilityRequest(
        name="my-new-capacity",
        type="Microsoft.Fabric/capacities"
    )
)

if result.name_available:
    print("Name is available")
else:
    print(f"Name not available: {result.reason}")

List Available SKUs

skus = client.fabric_capacities.list_skus(
    resource_group_name=resource_group,
    capacity_name=capacity_name
)

for sku in skus:
    print(f"SKU: {sku.name} - Tier: {sku.tier}")

Client Operations

OperationMethod
client.fabric_capacitiesCapacity CRUD operations
client.operationsList available operations

Fabric SKUs

SKUDescriptionCUs
F2Entry level2 Capacity Units
F4Small4 Capacity Units
F8Medium8 Capacity Units
F16Large16 Capacity Units
F32X-Large32 Capacity Units
F642X-Large64 Capacity Units
F1284X-Large128 Capacity Units
F2568X-Large256 Capacity Units
F51216X-Large512 Capacity Units
F102432X-Large1024 Capacity Units
F204864X-Large2048 Capacity Units

Capacity States

StateDescription
ActiveCapacity is running
PausedCapacity is suspended (no billing)
ProvisioningBeing created
UpdatingBeing modified
DeletingBeing removed
FailedOperation failed

Long-Running Operations

All mutating operations are long-running (LRO). Use .result() to wait:

# Synchronous wait
capacity = client.fabric_capacities.begin_create_or_update(...).result()

# Or poll manually
poller = client.fabric_capacities.begin_create_or_update(...)
while not poller.done():
    print(f"Status: {poller.status()}")
    time.sleep(5)
capacity = poller.result()

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 DefaultAzureCredential for code that runs locally. Use a specific token credential for code that runs in Azure.
  4. Suspend unused capacities to reduce costs
  5. Start with smaller SKUs and scale up as needed
  6. Use tags for cost tracking and organization
  7. Check name availability before creating capacities
  8. Handle LRO properly — don't assume immediate completion
  9. Set up capacity admins — specify users who can manage workspaces
  10. Monitor capacity usage via Azure Monitor metrics

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.

レビュー

まだレビューはありません。使ってみた感想をお寄せください。

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