Azure Mgmt Fabric Py

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

Fabric SKUs

Capacity States

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

Source: microsoft/skills → .github/plugins/azure-sdk-python/skills/azure-mgmt-fabric-py/SKILL.md