Azure Functions

Azure Functions is a serverless compute service that runs event-driven code without managing infrastructure. Its unique binding system connects to Azure services declaratively, and Durable Functions enable complex stateful workflows.

25 stars

Best use case

Azure Functions is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Azure Functions is a serverless compute service that runs event-driven code without managing infrastructure. Its unique binding system connects to Azure services declaratively, and Durable Functions enable complex stateful workflows.

Teams using Azure Functions should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/azure-functions/SKILL.md --create-dirs "https://raw.githubusercontent.com/ComeOnOliver/skillshub/main/skills/TerminalSkills/skills/azure-functions/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/azure-functions/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How Azure Functions Compares

Feature / AgentAzure FunctionsStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Azure Functions is a serverless compute service that runs event-driven code without managing infrastructure. Its unique binding system connects to Azure services declaratively, and Durable Functions enable complex stateful workflows.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# Azure Functions

Azure Functions is a serverless compute service that runs event-driven code without managing infrastructure. Its unique binding system connects to Azure services declaratively, and Durable Functions enable complex stateful workflows.

## Core Concepts

- **Trigger** — what causes a function to run (HTTP, timer, queue, blob, etc.)
- **Input Binding** — declaratively read data from a service when function runs
- **Output Binding** — declaratively write data to a service after function runs
- **Function App** — a container for one or more functions sharing configuration
- **Hosting Plan** — Consumption (pay-per-execution), Premium, or Dedicated
- **Durable Functions** — extension for stateful orchestrations and workflows

## Project Setup

```bash
# Create a new function project
func init my-functions --worker-runtime node --language javascript
cd my-functions
```

```bash
# Create a new HTTP-triggered function
func new --name HandleWebhook --template "HTTP trigger" --authlevel anonymous
```

```bash
# Create Azure resources
az group create --name my-app-rg --location eastus

az storage account create \
  --name myappfuncstorage \
  --resource-group my-app-rg \
  --sku Standard_LRS

az functionapp create \
  --name my-app-functions \
  --resource-group my-app-rg \
  --storage-account myappfuncstorage \
  --consumption-plan-location eastus \
  --runtime node \
  --runtime-version 20 \
  --functions-version 4
```

## HTTP Functions

```javascript
// src/functions/handleWebhook.js — HTTP triggered function
const { app } = require('@azure/functions');

app.http('handleWebhook', {
    methods: ['POST'],
    authLevel: 'anonymous',
    route: 'webhooks/{source}',
    handler: async (request, context) => {
        const source = request.params.source;
        const body = await request.json();

        context.log(`Webhook from ${source}:`, body);

        // Process webhook
        const result = await processWebhook(source, body);

        return {
            status: 200,
            jsonBody: { received: true, id: result.id }
        };
    }
});
```

## Timer Functions

```javascript
// src/functions/dailyCleanup.js — runs on a CRON schedule
const { app } = require('@azure/functions');

app.timer('dailyCleanup', {
    schedule: '0 0 2 * * *', // 2:00 AM daily
    handler: async (myTimer, context) => {
        context.log('Running daily cleanup at', new Date().toISOString());

        const deleted = await cleanupExpiredSessions();
        context.log(`Deleted ${deleted} expired sessions`);
    }
});
```

## Queue Trigger with Output Binding

```javascript
// src/functions/processOrder.js — triggered by queue, writes to Cosmos DB
const { app, output } = require('@azure/functions');

const cosmosOutput = output.cosmosDB({
    databaseName: 'app-db',
    containerName: 'processed-orders',
    connection: 'CosmosDBConnection',
    createIfNotExists: true
});

app.storageQueue('processOrder', {
    queueName: 'order-queue',
    connection: 'AzureWebJobsStorage',
    return: cosmosOutput,
    handler: async (queueItem, context) => {
        context.log('Processing order:', queueItem.orderId);

        const processedOrder = {
            id: queueItem.orderId,
            ...queueItem,
            status: 'processed',
            processedAt: new Date().toISOString()
        };

        // Returned value goes to Cosmos DB via output binding
        return processedOrder;
    }
});
```

## Blob Trigger

```javascript
// src/functions/processImage.js — triggered when blob is uploaded
const { app } = require('@azure/functions');

app.storageBlob('processImage', {
    path: 'uploads/{name}',
    connection: 'AzureWebJobsStorage',
    handler: async (blob, context) => {
        const fileName = context.triggerMetadata.name;
        context.log(`Processing blob: ${fileName}, size: ${blob.length} bytes`);

        // Resize image, extract metadata, etc.
        await generateThumbnail(blob, fileName);
    }
});
```

## Durable Functions

```javascript
// src/functions/orderOrchestrator.js — orchestrate multi-step order processing
const { app } = require('@azure/functions');
const df = require('durable-functions');

// Orchestrator function
df.app.orchestration('orderOrchestrator', function* (context) {
    const order = context.df.getInput();

    // Step 1: Validate inventory
    const inventory = yield context.df.callActivity('checkInventory', order.items);
    if (!inventory.available) {
        yield context.df.callActivity('notifyCustomer', {
            orderId: order.id,
            message: 'Items out of stock'
        });
        return { status: 'cancelled', reason: 'out_of_stock' };
    }

    // Step 2: Process payment
    const payment = yield context.df.callActivity('processPayment', {
        amount: order.total,
        customerId: order.customerId
    });

    // Step 3: Ship order (with retry)
    const retryOptions = new df.RetryOptions(5000, 3); // 5s interval, 3 attempts
    const shipment = yield context.df.callActivityWithRetry(
        'shipOrder', retryOptions, order
    );

    // Step 4: Notify customer
    yield context.df.callActivity('notifyCustomer', {
        orderId: order.id,
        message: `Shipped! Tracking: ${shipment.trackingNumber}`
    });

    return { status: 'completed', tracking: shipment.trackingNumber };
});

// Activity functions
df.app.activity('checkInventory', { handler: async (items) => { /* ... */ } });
df.app.activity('processPayment', { handler: async (payment) => { /* ... */ } });
df.app.activity('shipOrder', { handler: async (order) => { /* ... */ } });
df.app.activity('notifyCustomer', { handler: async (notification) => { /* ... */ } });

// HTTP starter
app.http('startOrder', {
    route: 'orders/start',
    methods: ['POST'],
    extraInputs: [df.input.durableClient()],
    handler: async (req, context) => {
        const client = df.getClient(context);
        const order = await req.json();
        const instanceId = await client.startNew('orderOrchestrator', { input: order });
        return client.createCheckStatusResponse(req, instanceId);
    }
});
```

## Deployment

```bash
# Deploy to Azure
func azure functionapp publish my-app-functions
```

```bash
# Set application settings
az functionapp config appsettings set \
  --name my-app-functions \
  --resource-group my-app-rg \
  --settings "CosmosDBConnection=AccountEndpoint=..."
```

```bash
# View function logs
func azure functionapp logstream my-app-functions
```

## Best Practices

- Use bindings to avoid boilerplate for reading/writing Azure services
- Choose Consumption plan for sporadic workloads, Premium for consistent traffic
- Use Durable Functions for multi-step workflows instead of chaining queues
- Store connection strings in Application Settings, not code
- Set `FUNCTIONS_WORKER_PROCESS_COUNT` for CPU-bound workloads
- Use managed identities instead of connection strings where possible
- Enable Application Insights for monitoring and diagnostics
- Keep functions small and focused — one trigger, one purpose

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