Azure Durable Functions Patterns and Best Practices: The Ultimate Guide

Azure Durable Functions are a powerful extension of Azure Functions that allow you to define long-running, stateful function orchestrations in code. With Durable Functions, you can implement complex workflows and coordination patterns that would be difficult or impossible with regular stateless functions alone.

In this comprehensive guide, we‘ll cover everything you need to know to master Azure Durable Functions. I‘ll explain what they are, highlight their key benefits and use cases, walk through the most common orchestration patterns, and share some essential best practices you should follow. By the end of this article, you‘ll be equipped to build robust, scalable serverless applications with Durable Functions. Let‘s dive in!

What are Azure Durable Functions?

Durable Functions are an extension of Azure Functions that allow you to write stateful functions in a serverless environment. While regular Azure Functions are stateless (each invocation is independent and can‘t share data without an external store), Durable Functions have built-in state management and allow you to define long-running workflows as orchestrations.

An orchestration is a function that describes the steps in a multi-function workflow. You define the orchestration in code (C# or JavaScript) using the Durable Functions APIs. This orchestrator function can then call other regular or "activity" functions in a particular order while maintaining state between each step.

The Durable Functions extension handles all of the underlying plumbing like starting/stopping orchestrations, replaying history to recover state, managing timers and external events, etc. You simply define your workflow logic in code and let the Durable Functions runtime take care of the rest!

Benefits and Use Cases

There are several compelling reasons to use Durable Functions:

1. They allow you to define complex, long-running workflows in code. No more stitching together disparate functions or relying on external services.

2. Orchestrations are stateful and can survive failures/restarts. If a host crashes, the orchestration will resume from its last checkpoint.

3. Orchestrations can wait for external events and timers, enabling scenarios like approval flows and monitoring.

4. Fan-out/fan-in patterns allow orchestrations to execute functions in parallel and aggregate the results.

5. Orchestrations can be long-running (days or even months) making them suitable for many workflow scenarios.

Some common use cases for Durable Functions include:

• Sequential processing pipelines
• Parallel processing with aggregation
• Monitoring and polling
• Approval workflows with timeouts
• Data aggregation from multiple sources
• Failure compensation and complex error handling

Essentially, if you have any multi-step workflow or process that requires coordination, state management, or complex error handling, Durable Functions are a great fit. They allow you to define your orchestrations and activities entirely in code and let the runtime handle the heavy lifting.

Now that we understand what Durable Functions are and why we might use them, let‘s look at some of the most common orchestration patterns and how to implement them.

Function Chaining Pattern

Function chaining is the most basic orchestration pattern. It allows you to chain together a sequence of functions where the output of one becomes the input to the next. The orchestrator invokes each function in order, passing the result of the previous function as input to the next.

Here‘s a simple example of function chaining in C#:

[FunctionName("ChainingSample")]
public static async Task<object> Run(
    [OrchestrationTrigger] DurableOrchestrationContext context)
{
    try
    {
        var x = await context.CallActivityAsync<object>("F1", null);
        var y = await context.CallActivityAsync<object>("F2", x);
        var z = await context.CallActivityAsync<object>("F3", y);
        return  await context.CallActivityAsync<object>("F4", z);
    }
    catch (Exception)
    {
        // Error handling or compensation goes here.
    }
}

In this example, the orchestrator function calls four activity functions (F1, F2, F3, F4) in sequence. The output of each function is passed as the input to the next using the context.CallActivityAsync method. If any of the functions throw an exception, the catch block can handle the error or perform compensating actions.

Chaining functions like this is much simpler and more reliable than stitching together separate functions with queues or events. The orchestrator provides a single place to define the workflow and handles all the state management and error handling.

Fan-out/Fan-in Pattern

The fan-out/fan-in pattern allows you to execute multiple functions in parallel and then aggregate the results. The orchestrator will "fan-out" by scheduling multiple activity functions to run concurrently. It then "fans-in" by waiting for all the parallel activities to finish and aggregating the results.

Here‘s an example of the fan-out/fan-in pattern in C#:

[FunctionName("FanOutFanIn")]
public static async Task Run(
    [OrchestrationTrigger] DurableOrchestrationContext context)
{
    var parallelTasks = new List<Task<int>>();

    // Get a list of N work items to process in parallel.
    object[] workBatch = await context.CallActivityAsync<object[]>("F1", null);
    for (int i = 0; i < workBatch.Length; i++)
    {
        Task<int> task = context.CallActivityAsync<int>("F2", workBatch[i]);
        parallelTasks.Add(task);
    }

    await Task.WhenAll(parallelTasks);

    // Aggregate all N outputs and send result to F3.
    int sum = parallelTasks.Sum(t => t.Result);
    await context.CallActivityAsync("F3", sum);
}

In this example, the orchestrator first calls an activity function F1 to get a batch of work items. It then schedules F2 to process each work item in parallel, collecting the tasks into a List<Task<int>>. The orchestrator waits for all the parallel tasks to complete using Task.WhenAll. Finally, it sums the results and passes the sum to activity function F3.

The Durable Functions runtime will correctly handle scheduling, executing, and aggregating all the parallel activity functions, making complex parallel processing patterns much easier to implement.

Asynchronous HTTP API Pattern

Durable Functions can be used to implement long-running HTTP APIs that follow the async request-reply pattern. An HTTP-triggered function can start an orchestrator and then immediately return a 202 response with a location header pointing to a status endpoint. The client can then poll the status endpoint to query the status of the long-running operation.

Here‘s a simplified example:

[FunctionName("StartNewOrchestrator")]
public static async Task<HttpResponseMessage> Run(
    [HttpTrigger(AuthorizationLevel.Function, "post", Route = "orchestrators/{functionName}")] HttpRequestMessage req,
    [DurableClient] IDurableOrchestrationClient starter,
    string functionName,
    ILogger log)
{
    // Function input comes from the request content.
    object eventData = await req.Content.ReadAsAsync<object>();
    string instanceId = await starter.StartNewAsync(functionName, eventData);

    log.LogInformation($"Started orchestration with ID = ‘{instanceId}‘.");

    return starter.CreateCheckStatusResponse(req, instanceId);
}

This HTTP-triggered function starts a new orchestration when it receives a request. The orchestrator function name and input are read from the request. It then starts the orchestrator using starter.StartNewAsync and returns an HTTP 202 response with the instance ID of the orchestration.

The client receives the 202 response with a location header they can use to poll for the orchestration status. The Durable Functions extension automatically creates this status endpoint, which returns a 200 response with the output of the orchestration when it completes, or a 202 if it‘s still running.

This pattern is useful for kicking off long-running processes from an HTTP request without blocking the client. The client can start the operation and then poll for the result as needed.

Monitor Pattern

The monitor pattern allows you to implement recurring processes like polling or cleanup jobs using Durable Functions. The orchestrator wakes up on a defined schedule, performs some work, and then goes back to sleep until the next interval.

Here‘s an example of an orchestrator function that implements the monitor pattern:

[FunctionName("MonitorJob")]
public static async Task Run(
    [OrchestrationTrigger] IDurableOrchestrationContext context)
{
    int pollingInterval = GetPollingInterval();
    DateTime expiryTime = GetExpiryTime();

    while (context.CurrentUtcDateTime < expiryTime)
    {
        var jobStatus = await context.CallActivityAsync<string>("GetJobStatus", null);
        if (jobStatus == "Completed")
        {
            // Perform action when condition met
            await context.CallActivityAsync("SendAlert", null);
            break;
        }

        // Orchestration sleeps until next poll
        var nextCheck = context.CurrentUtcDateTime.AddSeconds(pollingInterval);
        await context.CreateTimer(nextCheck, CancellationToken.None);
    }

    // Perform final action
    await context.CallActivityAsync("SendAlert", null);
}

This orchestrator function polls a job status using an activity function GetJobStatus on a defined interval. If the job is completed, it sends an alert and exits. If the polling expires, it sends a final alert. Between each check, the orchestrator sleeps by creating a durable timer with context.CreateTimer.

This pattern is useful for any kind of recurring job or process that needs to run on a schedule. The Durable Functions runtime will ensure the orchestrator wakes up on schedule and resumes from where it left off each time.

Human Interaction Pattern

Many processes require some form of human interaction, like an approval step in a workflow. Durable Functions can implement human interaction patterns by combining durable timers with external events.

Here‘s an example of an approval process implemented with Durable Functions:

[FunctionName("ApprovalWorkflow")]
public static async Task Run(
    [OrchestrationTrigger] IDurableOrchestrationContext context)
{
    await context.CallActivityAsync("RequestApproval", null);

    using (var timeoutCts = new CancellationTokenSource())
    {
        DateTime dueTime = context.CurrentUtcDateTime.AddHours(72);
        Task durableTimeout = context.CreateTimer(dueTime, timeoutCts.Token);

        Task<bool> approvalEvent = context.WaitForExternalEvent<bool>("ApprovalEvent");
        if (approvalEvent == await Task.WhenAny(approvalEvent, durableTimeout))
        {
            timeoutCts.Cancel();
            await context.CallActivityAsync("ProcessApproval", approvalEvent.Result);
        }
        else
        {
            await context.CallActivityAsync("Escalate", null);
        }
    }
}

In this example, the orchestrator first requests approval by calling an activity function. It then creates a durable timer that will fire in 72 hours, representing the approval timeout. The orchestrator then waits for an external event called "ApprovalEvent" using context.WaitForExternalEvent.

The Task.WhenAny logic races the approval event against the timeout. If the approval event is received before the timeout, the orchestrator cancels the timeout and processes the approval. If the timeout fires first, the orchestrator escalates the approval request.

External clients can "raise" the approval event at the right time by calling the Durable Functions APIs, e.g.:

[FunctionName("RaiseApprovalEvent")]
public static async Task Run(
    [HttpTrigger] IDurableOrchestrationClient client,
    bool result)
{
    await client.RaiseEventAsync("ApprovalWorkflow", "ApprovalEvent", result);   
}

This pattern makes it easy to implement long-running processes that require human interaction and have defined timeout periods. The ability to wait for external events and the presence of durable timers allows complex approval logic to be modeled entirely in code.

Best Practices

Here are some key best practices to keep in mind when working with Durable Functions:

Versioning

It‘s important to version your Durable Functions, especially if you expect orchestrations to be long-running. If you deploy an update to your app that changes an orchestrator‘s code, in-flight instances will fail when they try to replay using the new code. The solution is to create a new version of your orchestrator function and leave the old version in place (sometimes called "side-by-side" deployment).

Monitoring with Application Insights

Durable Functions emit structured logging events to Azure Application Insights. You can use Application Insights to monitor the health and progress of your orchestrations, set up alerts, and visualize the relationships between functions.

Be sure to configure your Durable Functions app with the Application Insights instrumentation key to enable this rich tracing.

Managing Orchestrations

Durable Functions provide an HTTP API and a set of binding types that allow you to manage orchestrations. For example, you can start, query, suspend, resume, and terminate orchestrations using these APIs.

Here are some of the key management operations:

• StartNewAsync: Starts a new instance of an orchestrator function.
• GetStatusAsync: Gets the status of an orchestration instance.
• RaiseEventAsync: Sends an event notification to a waiting orchestration instance.
• TerminateAsync: Terminates a running orchestration instance.
• PurgeInstanceHistoryAsync: Purges the history for a completed orchestration instance.

These APIs allow you to build rich management experiences around your Durable Functions and provide operational control over running instances.

Error Handling and Compensation

Because orchestrations are long-running, it‘s crucial to anticipate and handle errors. Any unhandled exceptions will cause the orchestration to fail and suspend. You‘ll need to either handle the error or terminate the failed instance.

In many cases, you‘ll also need to define compensation logic to undo any partially completed work if an error occurs partway through an orchestration. The Durable Functions APIs provide ways to define try/catch blocks and compensation actions.

Conclusion

Azure Durable Functions are a powerful tool for building long-running, stateful workflows in a serverless environment. They allow you to define complex orchestrations entirely in code and provide built-in state management, reliability, and scalability.

In this guide, we covered the key benefits and use cases of Durable Functions, explored several common orchestration patterns, and outlined some best practices to follow.

Whether you‘re building a simple function chaining workflow, a complex fan-out/fan-in parallel processing job, an async HTTP API, a recurring monitor process, or a human interaction workflow, Durable Functions provide the tools you need.

By understanding these patterns and best practices, you‘ll be well-equipped to design and build stateful serverless applications with Azure Durable Functions. The possibilities are endless – get started today!