azure-identity-py

Azure Identity SDK for Python

Authentication library for Azure SDK clients using Microsoft Entra ID (formerly Azure AD).

Installation

pip install azure-identity

Environment Variables

# Service Principal (for production/​CI)
AZURE_TENANT_ID=<your-tenant-id>
AZURE_CLIENT_ID=<your-client-id>
AZURE_CLIENT_SECRET=<your-client-secret>

# User-assigned Managed Identity (optional)
AZURE_CLIENT_ID=<managed-identity-client-id>

DefaultAzureCredential

The recommended credential for most scenarios. Tries multiple authentication methods in order:

from azure.identity import DefaultAzureCredential
from azure.storage.blob import BlobServiceClient

# Works in local dev AND production without code changes
credential = DefaultAzureCredential()

client = BlobServiceClient(
    account_url="https://<account>.blob.core.windows.net",
    credential=credential
)

Credential Chain Order

Customizing DefaultAzureCredential

# Exclude credentials you don't need
credential = DefaultAzureCredential(
    exclude_environment_credential=True,
    exclude_shared_token_cache_credential=True,
    managed_identity_client_id="<user-assigned-mi-client-id>"  # For user-assigned MI
)

# Enable interactive browser (disabled by default)
credential = DefaultAzureCredential(
    exclude_interactive_browser_credential=False
)

Specific Credential Types

ManagedIdentityCredential

For Azure-hosted resources (VMs, App Service, Functions, AKS):

from azure.identity import ManagedIdentityCredential

# System-assigned managed identity
credential = ManagedIdentityCredential()

# User-assigned managed identity
credential = ManagedIdentityCredential(
    client_id="<user-assigned-mi-client-id>"
)

ClientSecretCredential

For service principal with secret:

from azure.identity import ClientSecretCredential

credential = ClientSecretCredential(
    tenant_id=os.environ["AZURE_TENANT_ID"],
    client_id=os.environ["AZURE_CLIENT_ID"],
    client_secret=os.environ["AZURE_CLIENT_SECRET"]
)

AzureCliCredential

Uses the account from az login:

from azure.identity import AzureCliCredential

credential = AzureCliCredential()

ChainedTokenCredential

Custom credential chain:

from azure.identity import (
    ChainedTokenCredential,
    ManagedIdentityCredential,
    AzureCliCredential
)

# Try managed identity first, fall back to CLI
credential = ChainedTokenCredential(
    ManagedIdentityCredential(client_id="<user-assigned-mi-client-id>"),
    AzureCliCredential()
)

Credential Types Table

Getting Tokens Directly

from azure.identity import DefaultAzureCredential

credential = DefaultAzureCredential()

# Get token for a specific scope
token = credential.get_token("https://management.azure.com/.default")
print(f"Token expires: {token.expires_on}")

# For Azure Database for PostgreSQL
token = credential.get_token("https://ossrdbms-aad.database.windows.net/.default")

Async Client

from azure.identity.aio import DefaultAzureCredential
from azure.storage.blob.aio import BlobServiceClient

async def main():
    credential = DefaultAzureCredential()
    
    async with BlobServiceClient(
        account_url="https://<account>.blob.core.windows.net",
        credential=credential
    ) as client:
        # ... async operations
        pass
    
    await credential.close()

Best Practices

1. Use DefaultAzureCredential for code that runs locally and in Azure
2. Never hardcode credentials — use environment variables or managed identity
3. Prefer managed identity in production Azure deployments
4. Use ChainedTokenCredential when you need a custom credential order
5. Close async credentials explicitly or use context managers
6. Set AZURE_CLIENT_ID for user-assigned managed identities
7. Exclude unused credentials to speed up authentication

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 Identity 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-identity-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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