Azure Functions Developer Guide

Table of Contents

Introduction to Azure Functions

Azure Functions is a serverless compute service that allows you to run small pieces of code, or "functions," in the cloud without needing to provision or manage infrastructure. It's a powerful event-driven compute platform that can be integrated with a wide range of Azure services and third-party data sources.

Key benefits include:

  • Event-driven: Functions are triggered by events, such as HTTP requests, timer schedules, or messages arriving in a queue.
  • Scalable: Azure Functions automatically scales your application by the number of incoming events.
  • Cost-effective: You only pay for the resources consumed when your functions are running.
  • Polyglot: Supports multiple programming languages, including C#, JavaScript, Python, Java, and PowerShell.

Getting Started

To begin developing Azure Functions, you'll need:

The basic workflow involves creating a new function project, defining a function with a trigger and bindings, and then deploying it to Azure.

Creating your first function

Using the Azure Functions Core Tools, you can create a new project with a template:


func init MyFunctionProj --worker-runtime dotnet --language csharp
cd MyFunctionProj
func new --name HttpTriggerExample --template "HTTP trigger"

Development Models

Azure Functions supports several development models, each with its own advantages:

1. In-Process Model

Runs your code within the same process as the Functions host. This model offers lower latency and simpler local debugging. It's available for languages like .NET (versions that support in-process execution).

2. Isolated Worker Model

Runs your code in a separate process. This provides greater flexibility, allowing you to use different language versions and libraries independently of the Functions host. It's the default for .NET 6+ and a good choice for Node.js, Python, and Java.

3. Durable Functions

An extension of Azure Functions that allows you to write stateful functions in a serverless environment. You can coordinate multiple functions to form stateful workflows, orchestrate long-running processes, and build complex patterns like fan-out/fan-in.

Learn more about Durable Functions.

Triggers and Bindings

Triggers define how a function is invoked, while bindings allow you to declaratively connect your function to other Azure services and data sources without writing custom integration code.

Common Triggers:

  • HTTP Trigger: Invoked by an HTTP request.
  • Timer Trigger: Runs on a schedule (using CRON expressions).
  • Queue Trigger: Invoked when a message is added to a storage queue.
  • Blob Trigger: Invoked when a new or updated blob is detected in Azure Blob Storage.
  • Cosmos DB Trigger: Invoked when changes are detected in a Cosmos DB collection.

Common Bindings:

  • Input Bindings: Fetch data from services (e.g., reading from a database, retrieving a blob).
  • Output Bindings: Send data to services (e.g., writing to a queue, saving to a database).

Bindings simplify your code by abstracting away the complexities of interacting with external services.


{
  "scriptFile": "__init__.py",
  "bindings": [
    {
      "authLevel": "function",
      "type": "httpTrigger",
      "direction": "in",
      "name": "req",
      "methods": [
        "get",
        "post"
      ]
    },
    {
      "type": "http",
      "direction": "out",
      "name": "res"
    },
    {
      "type": "blob",
      "direction": "in",
      "name": "inputBlob",
      "path": "mycontainer/{name}.txt",
      "connection": "AzureWebJobsStorage"
    }
  ]
}

Runtime Considerations

Azure Functions runs on different hosting plans, impacting performance, scalability, and cost:

  • Consumption Plan: Pay-per-execution model. Scales automatically, but functions can experience cold starts.
  • Premium Plan: Pre-warmed instances to reduce cold starts, VNet connectivity, and longer run durations.
  • App Service Plan: Run functions on dedicated virtual machines, similar to traditional web apps.

Understanding these plans is crucial for optimizing performance and cost for your specific workload.

Deployment

You can deploy Azure Functions to the cloud using various methods:

  • Azure Functions Core Tools: Command-line deployment.
  • Azure CLI: Programmatic deployment.
  • Visual Studio / VS Code: Integrated deployment workflows.
  • CI/CD Pipelines: Automate deployments with Azure DevOps, GitHub Actions, etc.

For production deployments, consider strategies like deployment slots for zero-downtime updates.

Monitoring and Debugging

Effective monitoring and debugging are essential for maintaining healthy functions:

  • Application Insights: Provides deep insights into your function's performance, usage, and errors.
  • Live Metrics: Real-time monitoring of requests, dependencies, and exceptions.
  • Logging: Implement structured logging within your functions to capture detailed execution information.
  • Local Debugging: Use the Azure Functions Core Tools to run and debug functions on your local machine.

Set up alerts in Application Insights to be notified of critical issues.

Security

Securing your Azure Functions is paramount:

  • Authentication and Authorization: Use API keys, OAuth, or Azure AD for HTTP triggers.
  • Managed Identities: Allow your functions to authenticate to other Azure services without storing credentials.
  • Key Vault: Store and manage secrets, keys, and certificates securely.
  • Network Security: Configure VNet integration and firewalls to restrict access.

Best Practices

  • Keep functions small and focused: Each function should perform a single task.
  • Handle exceptions gracefully: Implement robust error handling.
  • Optimize for cold starts: Choose appropriate hosting plans and consider warm-up techniques.
  • Use asynchronous programming: Especially for I/O-bound operations.
  • Manage dependencies carefully: Avoid large or conflicting libraries.
  • Implement robust logging and monitoring.