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azure-functions skill

/skills/azure-functions

This skill helps you create and manage Azure Functions with triggers, bindings, authentication, and monitoring for scalable serverless apps.

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---
name: azure-functions
description: Create serverless functions on Azure with triggers, bindings, authentication, and monitoring. Use for event-driven computing without managing infrastructure.
---

# Azure Functions

## Overview

Azure Functions enables serverless computing on Microsoft Azure. Build event-driven applications with automatic scaling, flexible bindings to various Azure services, and integrated monitoring through Application Insights.

## When to Use

- HTTP APIs and webhooks
- Message-driven processing (Service Bus, Event Hub)
- Scheduled jobs and CRON expressions
- File and blob processing
- Queue-based workflows
- Real-time data processing
- Microservices and backend logic
- Integration with Azure ecosystem services

## Implementation Examples

### 1. **Azure Function Creation with Azure CLI**

```bash
# Install Azure Functions Core Tools
curl https://aka.ms/install-artifacts-ubuntu.sh | bash

# Login to Azure
az login

# Create resource group
az group create --name myapp-rg --location eastus

# Create storage account (required for Functions)
az storage account create \
  --name myappstore \
  --location eastus \
  --resource-group myapp-rg \
  --sku Standard_LRS

# Create Function App
az functionapp create \
  --resource-group myapp-rg \
  --consumption-plan-location eastus \
  --runtime node \
  --runtime-version 18 \
  --functions-version 4 \
  --name myapp-function \
  --storage-account myappstore

# Create function in app
func new --name HttpTrigger --template "HTTP trigger"

# Configure authentication
az functionapp auth update \
  --resource-group myapp-rg \
  --name myapp-function \
  --enabled true \
  --action RedirectToLoginPage \
  --default-provider AzureActiveDirectory

# Deploy function
func azure functionapp publish myapp-function

# Check deployment
az functionapp list --output table

# Get function details
az functionapp function show \
  --resource-group myapp-rg \
  --name myapp-function \
  --function-name HttpTrigger
```

### 2. **Azure Function Implementation (Node.js)**

```javascript
// HttpTrigger/index.js
module.exports = async function (context, req) {
  context.log('HTTP trigger function processed request.');

  // Extract request data
  const name = req.query.name || (req.body && req.body.name);
  const requestId = context.traceContext.traceparent;

  try {
    // Validate input
    if (!name) {
      return {
        status: 400,
        body: { error: 'Name parameter is required' }
      };
    }

    // Business logic
    const response = {
      message: `Hello ${name}!`,
      timestamp: new Date().toISOString(),
      requestId: requestId
    };

    // Log to Application Insights
    context.log({
      level: 'info',
      message: 'Request processed successfully',
      name: name,
      requestId: requestId
    });

    return {
      status: 200,
      headers: {
        'Content-Type': 'application/json',
        'X-Request-ID': requestId
      },
      body: response
    };
  } catch (error) {
    context.log.error('Error processing request:', error);

    return {
      status: 500,
      body: { error: 'Internal server error' }
    };
  }
};

// TimerTrigger/index.js
module.exports = async function (context, myTimer) {
  const timeStamp = new Date().toISOString();

  if (myTimer.isPastDue) {
    context.log('Timer function is running late!');
  }

  // Process scheduled job
  context.log(`Timer trigger function ran at ${timeStamp}`);
  context.log('Processing batch job...');

  // Simulate work
  await new Promise(resolve => setTimeout(resolve, 1000));

  context.log('Batch job completed');
};

// ServiceBusQueueTrigger/index.js
module.exports = async function (context, mySbMsg) {
  context.log('ServiceBus queue trigger function processed message:', mySbMsg);

  try {
    const messageBody = typeof mySbMsg === 'string' ? JSON.parse(mySbMsg) : mySbMsg;

    // Process message
    await processMessage(messageBody);

    context.log('Message processed successfully');
  } catch (error) {
    context.log.error('Error processing message:', error);
    throw error; // Re-queue message
  }
};

async function processMessage(messageBody) {
  // Business logic here
  return true;
}
```

### 3. **Azure Functions with Terraform**

```hcl
# functions.tf
terraform {
  required_providers {
    azurerm = {
      source  = "hashicorp/azurerm"
      version = "~> 3.0"
    }
  }
}

provider "azurerm" {
  features {
    virtual_machine {
      delete_os_disk_on_delete            = true
      graceful_shutdown                   = false
      skip_shutdown_and_force_delete       = false
    }
  }
}

variable "environment" {
  default = "dev"
}

variable "location" {
  default = "eastus"
}

# Resource group
resource "azurerm_resource_group" "main" {
  name     = "myapp-rg-${var.environment}"
  location = var.location
}

# Storage account for Function App
resource "azurerm_storage_account" "function_storage" {
  name                     = "myappstore${var.environment}"
  resource_group_name      = azurerm_resource_group.main.name
  location                 = azurerm_resource_group.main.location
  account_tier             = "Standard"
  account_replication_type = "LRS"

  identity {
    type = "SystemAssigned"
  }

  tags = {
    environment = var.environment
  }
}

# Application Insights
resource "azurerm_application_insights" "main" {
  name                = "myapp-insights-${var.environment}"
  location            = azurerm_resource_group.main.location
  resource_group_name = azurerm_resource_group.main.name
  application_type    = "web"

  retention_in_days = 30
}

# App Service Plan
resource "azurerm_service_plan" "function_plan" {
  name                = "myapp-plan-${var.environment}"
  location            = azurerm_resource_group.main.location
  resource_group_name = azurerm_resource_group.main.name
  os_type             = "Linux"
  sku_name            = "Y1" # Consumption plan

  tags = {
    environment = var.environment
  }
}

# Function App
resource "azurerm_linux_function_app" "main" {
  name                = "myapp-function-${var.environment}"
  location            = azurerm_resource_group.main.location
  resource_group_name = azurerm_resource_group.main.name
  service_plan_id     = azurerm_service_plan.function_plan.id

  storage_account_name       = azurerm_storage_account.function_storage.name
  storage_account_access_key = azurerm_storage_account.function_storage.primary_access_key

  app_settings = {
    APPINSIGHTS_INSTRUMENTATIONKEY             = azurerm_application_insights.main.instrumentation_key
    APPLICATIONINSIGHTS_CONNECTION_STRING      = azurerm_application_insights.main.connection_string
    AzureWebJobsStorage                        = azurerm_storage_account.function_storage.primary_blob_connection_string
    WEBSITE_NODE_DEFAULT_VERSION               = "~18"
    FUNCTIONS_EXTENSION_VERSION                = "~4"
    FUNCTIONS_WORKER_RUNTIME                   = "node"
    ENABLE_INIT_LOGGING                        = true
    WEBSITE_RUN_FROM_PACKAGE                   = 1
  }

  site_config {
    application_insights_key             = azurerm_application_insights.main.instrumentation_key
    application_insights_connection_string = azurerm_application_insights.main.connection_string

    cors {
      allowed_origins = ["https://example.com"]
    }

    http2_enabled = true
  }

  https_only = true
  identity {
    type = "SystemAssigned"
  }

  tags = {
    environment = var.environment
  }
}

# Key Vault for secrets
resource "azurerm_key_vault" "function_secrets" {
  name                = "myappkv${var.environment}"
  location            = azurerm_resource_group.main.location
  resource_group_name = azurerm_resource_group.main.name
  tenant_id           = data.azurerm_client_config.current.tenant_id
  sku_name            = "standard"

  access_policy {
    tenant_id = data.azurerm_client_config.current.tenant_id
    object_id = azurerm_linux_function_app.main.identity[0].principal_id

    secret_permissions = [
      "Get",
      "List"
    ]
  }

  tags = {
    environment = var.environment
  }
}

# Store database password in Key Vault
resource "azurerm_key_vault_secret" "db_password" {
  name         = "db-password"
  value        = "MySecurePassword123!"
  key_vault_id = azurerm_key_vault.function_secrets.id
}

# Diagnostic settings
resource "azurerm_monitor_diagnostic_setting" "function_logs" {
  name               = "function-logs"
  target_resource_id = azurerm_linux_function_app.main.id

  log_analytics_workspace_id = azurerm_log_analytics_workspace.main.id

  enabled_log {
    category = "FunctionAppLogs"
  }

  metric {
    category = "AllMetrics"
  }
}

# Log Analytics Workspace
resource "azurerm_log_analytics_workspace" "main" {
  name                = "myapp-logs-${var.environment}"
  location            = azurerm_resource_group.main.location
  resource_group_name = azurerm_resource_group.main.name
  sku                 = "PerGB2018"

  retention_in_days = 30
}

data "azurerm_client_config" "current" {}

output "function_app_url" {
  value = "https://${azurerm_linux_function_app.main.default_hostname}"
}

output "app_insights_key" {
  value     = azurerm_application_insights.main.instrumentation_key
  sensitive = true
}
```

### 4. **Function Bindings Configuration**

```json
{
  "scriptFile": "index.js",
  "bindings": [
    {
      "authLevel": "anonymous",
      "type": "httpTrigger",
      "direction": "in",
      "name": "req",
      "methods": ["get", "post"],
      "route": "api/{*route}"
    },
    {
      "type": "http",
      "direction": "out",
      "name": "$return"
    },
    {
      "type": "queue",
      "direction": "out",
      "name": "myQueueItem",
      "queueName": "myqueue",
      "connection": "AzureWebJobsStorage"
    },
    {
      "type": "serviceBus",
      "direction": "in",
      "name": "mySbMsg",
      "queueName": "myqueue",
      "connection": "ServiceBusConnection",
      "cardinality": "one"
    },
    {
      "type": "blob",
      "direction": "in",
      "name": "inputBlob",
      "path": "input/{name}",
      "connection": "AzureWebJobsStorage"
    },
    {
      "type": "blob",
      "direction": "out",
      "name": "outputBlob",
      "path": "output/{name}",
      "connection": "AzureWebJobsStorage"
    }
  ]
}
```

## Best Practices

### ✅ DO
- Use managed identity for Azure services
- Store secrets in Key Vault
- Enable Application Insights
- Implement idempotent functions
- Use durable functions for long-running operations
- Handle exceptions and failures
- Monitor function execution
- Use bindings instead of SDK calls

### ❌ DON'T
- Store secrets in code or configuration
- Ignore Application Insights
- Create functions without error handling
- Use blocking operations
- Create long-running functions without Durable Functions
- Ignore monitoring and logging

## Monitoring

- Application Insights for tracing and metrics
- Azure Monitor for overall health
- Log Analytics for log analysis
- Function metrics (execution count, duration)
- Custom telemetry and events

## Resources

- [Azure Functions Documentation](https://docs.microsoft.com/en-us/azure/azure-functions/)
- [Azure Functions Best Practices](https://docs.microsoft.com/en-us/azure/azure-functions/functions-best-practices)
- [Azure Key Vault Integration](https://docs.microsoft.com/en-us/azure/azure-functions/security-concepts)

Overview

This skill helps you create, configure, and deploy Azure Functions for event-driven serverless workloads. It covers CLI and Terraform provisioning, common trigger and binding patterns, authentication, and integrated monitoring with Application Insights. Use it to build scalable APIs, background processors, and scheduled jobs without managing infrastructure.

How this skill works

The skill shows practical steps to provision resources (resource group, storage, Function App) using az CLI or Terraform, create function code (HTTP, timer, Service Bus) and configure bindings. It explains authentication (managed identity, AAD) and telemetry setup with Application Insights and Log Analytics for tracing and metrics. Deployment and operational checks are demonstrated using func and az commands.

When to use it

  • Expose lightweight HTTP APIs, webhooks, or serverless backends
  • Process messages from Service Bus, Event Hub, or storage queues
  • Run scheduled jobs and CRON-driven tasks via Timer triggers
  • Perform file/blob processing and ETL-style jobs
  • Implement background microservices and event-driven workflows

Best practices

  • Use managed identities and store secrets in Key Vault, not in code
  • Enable Application Insights and Log Analytics for tracing and metrics
  • Make functions idempotent and implement robust error handling
  • Prefer bindings for service integration instead of direct SDK use
  • Use Durable Functions for long-running or stateful workflows

Example use cases

  • HTTP-triggered API that returns personalized responses and logs request IDs
  • Timer-triggered batch job to aggregate data and push results to storage
  • Service Bus queue processor that deserializes messages and invokes business logic
  • Blob-triggered image processor that writes outputs to another container
  • Provision a production-ready Function App with Terraform, monitoring, and Key Vault integration

FAQ

How do I secure function endpoints?

Use Azure AD authentication or function-level keys. Prefer Azure AD with managed identities for backend service access and store tokens/secrets in Key Vault.

When should I use Durable Functions?

Use Durable Functions for long-running processes, stateful orchestrations, or complex retry workflows that exceed typical execution time limits.