Azure Durable Functions

What is a Durable Function?

A Durable Function is an extension of Azure Functions that allows you to write stateful workflows in a serverless environment. Durable Functions are part of the Durable Task Framework, which enables you to chain function calls, handle retries, and execute long-running processes without worrying about the limitations of the traditional stateless Azure Functions.

With Durable Functions, you can manage complex workflows that require coordination and long-running tasks like waiting for external events or managing retries.

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Key Concepts of Durable Functions:

1. Orchestrator Functions:

   • Purpose: Orchestrator functions define the workflow logic. They are responsible for calling other functions (called activity functions) in a defined order.
   • Behavior: Orchestrator functions are durable, meaning they can pause and resume without losing state. They are executed once and can call other functions in sequence, parallel, or even handle retries.
   • Example: You could have an orchestrator function that retrieves data from an Azure SQL Database, processes it, and then sends results to a downstream service.

2. Activity Functions:

   • Purpose: Activity functions are the actual units of work within the durable workflow. They execute the tasks like querying a database, calling an API, processing data, etc.
   • Behavior: Activity functions are stateless and run as normal Azure Functions.
   • Example: An activity function could perform an SQL query, send an email, or process a file.

3. Client Functions:

   • Purpose: These are regular Azure Functions that start the orchestration by calling the orchestrator function. They are typically HTTP-triggered and initiate the durable workflow.
   • Behavior: Client functions handle the initiation and monitor the progress or completion of the orchestration.
   • Example: An HTTP trigger might accept a request to start an orchestration that processes a file upload or runs a time-consuming SQL query.

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Key Features of Durable Functions:

1. Long-Running and State Preservation:

   • Durable Functions can run for extended periods (even days) and maintain state across retries and failures.
   • They can be paused and resumed by the Azure Durable Task framework, allowing them to handle long-running processes like waiting for external events or delays.

2. Resiliency and Retry Mechanism:

   • Durable Functions can automatically retry operations in case of failure or timeouts, ensuring that long-running operations are resilient.

3. Fan-Out and Fan-In Patterns:

   • Fan-Out: You can trigger multiple activities in parallel and wait for all of them to complete (useful for processing large datasets concurrently).
   • Fan-In: After the parallel operations, you can consolidate the results into a single output.

4. Human Intervention:

   • They support waiting for external events or human intervention before proceeding with the next step. For example, you could wait for a user to approve or review something before continuing the workflow.

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Example Workflow in Durable Functions:

Imagine a scenario where you need to query an Azure SQL Database and process the data over several steps, including retries for failures:

1. Client Function (HTTP Trigger): Accepts a request to start the process (e.g., querying a database).
2. Orchestrator Function:
   • Calls an Activity Function to query the database.
   • If the query takes a long time or is complex, it can be handled gracefully using Durable Functions.
   • Calls other activity functions to process the data (e.g., transformation, validation).
3. Activity Function:
   • Executes the query and processes the data.
   • Handles retries if an error occurs (e.g., network failure, SQL timeout).
4. Wait for External Event: If the process requires user confirmation or waiting for a response, the orchestrator can pause until the event is triggered.

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Example Code Snippet for Durable Functions:

Here’s a simplified example of how you might set up a Durable Function workflow with a SQL query and processing.

1. Orchestrator Function (DurableOrchestrator.cs):

[FunctionName("DurableOrchestrator")]
public static async Task RunOrchestrator(
    [OrchestrationTrigger] IDurableOrchestrationContext context)
{
    // Call the Activity Function to query the database
    var queryResult = await context.CallActivityAsync<string>("QueryDatabase", null);

    // Call another activity to process the data
    var processedData = await context.CallActivityAsync<string>("ProcessData", queryResult);

    return processedData;
}

2. Activity Function to Query Database (QueryDatabase.cs):

[FunctionName("QueryDatabase")]
public static string QueryDatabase([ActivityTrigger] string name, ILogger log)
{
    // Execute SQL query and return result
    return "Query result from DB";
}

3. Activity Function to Process Data (ProcessData.cs):

[FunctionName("ProcessData")]
public static string ProcessData([ActivityTrigger] string queryResult, ILogger log)
{
    // Process the data (e.g., transform, validate)
    return "Processed data: " + queryResult;
}

4. Client Function (HTTP Trigger):

[FunctionName("StartWorkflow")]
public static async Task<HttpResponseMessage> StartWorkflow(
    [HttpTrigger(AuthorizationLevel.Function, "get", "post")] HttpRequestMessage req,
    [DurableClient] IDurableOrchestrationClient starter,
    ILogger log)
{
    // Start the Durable Orchestration
    string instanceId = await starter.StartNewAsync("DurableOrchestrator", null);

    return starter.CreateCheckStatusResponse(req, instanceId);
}

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Key Considerations:

• Costs: While Durable Functions are great for long-running workflows, keep an eye on the execution time, as longer executions may increase costs, especially if using the Consumption plan.
• State Management: Durable Functions maintain state, so you don’t need to manage it manually (e.g., in a database or external system).
• Timeouts: Azure Durable Functions can run indefinitely, but they are subject to overall system limits, such as maximum execution duration.

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Conclusion:

Durable Functions are ideal for complex, long-running workflows that require state management, resiliency, and asynchronous execution. They can handle tasks that take hours or days, while still being highly scalable and cost-efficient.