Azure Fabric Management SDK for Python

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>
AZURE_RESOURCE_GROUP=<your-resource-group>

Authentication

from azure.identity import DefaultAzureCredential
from azure.mgmt.fabric import FabricMgmtClient
import os

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

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

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

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

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=["[email protected]"]
            )
        )
    )
).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. Use DefaultAzureCredential for authentication
2. Suspend unused capacities to reduce costs
3. Start with smaller SKUs and scale up as needed
4. Use tags for cost tracking and organization
5. Check name availability before creating capacities
6. Handle LRO properly — don't assume immediate completion
7. Set up capacity admins — specify users who can manage workspaces
8. Monitor capacity usage via Azure Monitor metrics

When to Use

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

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AGI Framework Integration

Adapted for @techwavedev/​agi-agent-kit Original source: antigravity-awesome-skills

Memory-First Protocol

Retrieve prior deployment configurations, rollback procedures, and incident post-mortems. Avoid re-discovering infrastructure patterns.

# Check for prior infrastructure context before starting
python3 execution/​memory_manager.py auto --query "deployment configuration and patterns for Azure Mgmt Fabric Py"

Storing Results

After completing work, store infrastructure decisions for future sessions:

python3 execution/​memory_manager.py store \
  --content "Deployment pipeline: configured blue-green deployment with health checks on port 8080" \
  --type technical --project <project> \
  --tags azure-mgmt-fabric-py devops

Multi-Agent Collaboration

Broadcast deployment changes so frontend and backend agents update their configurations accordingly.

python3 execution/​cross_agent_context.py store \
  --agent "<your-agent>" \
  --action "Deployed infrastructure changes — updated CI/​CD pipeline with new health check endpoints" \
  --project <project>

Playbook Integration

Use the ship-saas-mvp or full-stack-deploy playbook to sequence this skill with testing, documentation, and deployment verification.

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