Azure Function Development

Python
import azure.functions as func
import logging

def main(req: func.HttpRequest) -> func.HttpResponse:
    logging.info('Python HTTP trigger function processed a request.')
    
    name = req.params.get('name')
    if not name:
        try:
            req_body = req.get_json()
        except ValueError:
            pass
        else:
            name = req_body.get('name')
    
    if name:
        return func.HttpResponse(f"Hello, {name}!")
    else:
        return func.HttpResponse(
             "Please pass a name on the query string or in the request body",
             status_code=400
        )

Progress:

• Set up function app structure (func init)
• Create function template (func new)
• Configure bindings in function.json
• Implement business logic
• Add error handling and logging
• Configure application settings
• Test locally (func start)
• Deploy to Azure (func azure functionapp publish)
• Monitor and optimize

Project Structure

MyFunctionApp/
├── host.json
├── local.settings.json
├── requirements.txt
├── HttpTrigger/
│   ├── __init__.py
│   └── function.json
└── TimerTrigger/
    ├── __init__.py
    └── function.json

Example 1: HTTP Trigger with Cosmos DB Output Input: REST API endpoint that saves user data

JSON
{
  "bindings": [
    {
      "authLevel": "function",
      "type": "httpTrigger",
      "direction": "in",
      "name": "req",
      "methods": ["post"]
    },
    {
      "type": "cosmosDB",
      "direction": "out",
      "name": "doc",
      "databaseName": "Users",
      "collectionName": "UserData",
      "connectionStringSetting": "CosmosDBConnection"
    }
  ]
}

Example 2: Timer Trigger for Data Processing Input: Daily data cleanup job

Python
@app.schedule(schedule="0 0 2 * * *", arg_name="myTimer", run_on_startup=False)
def cleanup_old_data(myTimer: func.TimerRequest) -> None:
    logging.info('Cleanup function executed at %s', datetime.utcnow())
    # Cleanup logic here

Example 3: Queue Trigger with Service Bus Input: Process messages from Service Bus queue

Python
@app.service_bus_queue_trigger(arg_name="msg", queue_name="workitems",
                               connection="ServiceBusConnection")
def process_queue_message(msg: func.ServiceBusMessage):
    logging.info('Processing message: %s', msg.get_body().decode('utf-8'))

Performance:

• Keep functions stateless and lightweight
• Use async/await for I/O operations
• Implement proper connection pooling
• Set appropriate timeout values

Configuration:

• Use Key Vault references for secrets
• Environment-specific settings in Application Settings
• Connection strings in configuration, not code

Error Handling:

Python
try:
    # Function logic
    pass
except Exception as e:
    logging.error(f"Function failed: {str(e)}")
    return func.HttpResponse(
        "Internal server error",
        status_code=500
    )

Monitoring:

• Use Application Insights for telemetry
• Implement custom metrics and logs
• Set up alerts for failures and performance

• Cold starts: Avoid large dependencies; use Premium or Dedicated plans for consistent performance
• Timeout issues: Default timeout is 5 minutes for Consumption plan
• Memory leaks: Don't store state in global variables
• Connection limits: Reuse HTTP clients and database connections
• Large payloads: Use blob storage for files >100MB
• Synchronous blocking: Always use async for external calls
• Missing error handling: Functions should never throw unhandled exceptions
• Hardcoded secrets: Use managed identity and Key Vault integration