azure-functions
About
This Claude Skill enables developers to create serverless Azure Functions for event-driven computing without managing infrastructure. It supports triggers, bindings, authentication, and monitoring for building scalable applications like HTTP APIs, message processing, and scheduled jobs. Use it to quickly deploy serverless backends that integrate with Azure services using the Azure CLI and Functions Core Tools.
Documentation
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
# 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)
// 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 ${timeStamp}`);
context.log('Processing batch job...');
// Simulate work
await new Promise(resolve => setTimeout(resolve, 1000));
context.log('Batch job completed');
};
// ServiceBusQueueTrigger/index.js
module.exports = async function (context, mySbMsg) {
context.log('ServiceBus queue trigger function processed message:', mySbMsg);
try {
const messageBody = typeof mySbMsg === 'string' ? JSON.parse(mySbMsg) : mySbMsg;
// Process message
await processMessage(messageBody);
context.log('Message processed successfully');
} catch (error) {
context.log.error('Error processing message:', error);
throw error; // Re-queue message
}
};
async function processMessage(messageBody) {
// Business logic here
return true;
}
3. Azure Functions with Terraform
# functions.tf
terraform {
required_providers {
azurerm = {
source = "hashicorp/azurerm"
version = "~> 3.0"
}
}
}
provider "azurerm" {
features {
virtual_machine {
delete_os_disk_on_delete = true
graceful_shutdown = false
skip_shutdown_and_force_delete = false
}
}
}
variable "environment" {
default = "dev"
}
variable "location" {
default = "eastus"
}
# Resource group
resource "azurerm_resource_group" "main" {
name = "myapp-rg-${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://${azurerm_linux_function_app.main.default_hostname}"
}
output "app_insights_key" {
value = azurerm_application_insights.main.instrumentation_key
sensitive = true
}
4. Function Bindings Configuration
{
"scriptFile": "index.js",
"bindings": [
{
"authLevel": "anonymous",
"type": "httpTrigger",
"direction": "in",
"name": "req",
"methods": ["get", "post"],
"route": "api/{*route}"
},
{
"type": "http",
"direction": "out",
"name": "$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
Quick Install
/plugin add https://github.com/aj-geddes/useful-ai-prompts/tree/main/azure-functionsCopy and paste this command in Claude Code to install this skill
GitHub 仓库
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