Handling Dead Letter Queue Messages with Azure Functions: A Step-by-Step Guide

Design using Canva Team

Understanding the Problem

In many Azure Service Bus integration scenarios, messages can fail to process due to various reasons like receiver service bus connection issues, queue inaccessibility, or transaction failure while processing. These failed messages accumulate in the Dead Letter Queue (DLQ). To ensure data integrity and system reliability, it’s crucial to process these dead-lettered messages effectively.

Solution: We achieved using Azure Functions

Azure Functions, with its server less architecture, provides an ideal platform to build a function that processes messages from the DLQ, identifies the original request type, and performs necessary rollbacks or corrective actions.

Step-by-Step Implementation

Create a New Azure Function:

• Use the Azure Portal, Visual Studio, or Azure CLI to create a new Azure Function.
• Choose the isolated process model for better performance and isolation.
• Select the appropriate trigger for your function, such as a Timer Trigger or a Service Bus Trigger.

Configure the Function App:

• Ensure your function app has the necessary permissions to access the Service Bus namespace and the target queue.
• Add the required connection strings to your function app settings.

Define the Function Input Binding:

• Use the Service Bus trigger binding to receive messages from the DLQ.
• Specify the queue name with the $deadletterqueue suffix to target the DLQ:

[FunctionName("ProcessDLQMessage")]
public static async Task Run(
    [ServiceBusTrigger("queue-name/$deadletterqueue", Connection = "ServiceBusConnection")] ServiceBusMessage message,
    ILogger log)
{
    // ...
}

Extract Message Details:

• Deserialize the message body to extract relevant information about the original request.
• Identify the type of request based on the message content.

Implement Rollback Logic:

• Based on the identified request type, implement the corresponding rollback logic.
• This might involve compensating transactions, updating database records, or sending notification messages.
• Consider using retry logic with exponential backoff for transient failures.

Complete the Message: The system automatically deletes the message from the queue upon successful processing.

Sample Code: If any failure orders we are rollbacking those using the following function.

[FunctionName("ProcessDLQMessage")]
public static async Task Run(
    [ServiceBusTrigger("orders/$deadletterqueue", Connection = "ServiceBusConnection")] ServiceBusMessage message,
    ILogger log)
{
    try
    {
        var order = JsonConvert.DeserializeObject<Order>(message.Body.ToString());
        log.LogInformation($"Processing DLQ message for order {order.Id}");

        // Implement rollback logic based on order type
        if (order.Type == OrderType.Payment)
        {
            await RollbackPayment(order);
        }
        else if (order.Type == OrderType.Shipment)
        {
            await CancelShipment(order);
        }

        await message.CompleteAsync();
        log.LogInformation($"DLQ message processed successfully for order {order.Id}");
    }
    catch (Exception ex)
    {
        log.LogError(ex, "Error processing DLQ message");
        // Handle exceptions, potentially retry or dead-letter the message again
    }
}

Remember to tailor your implementation based on specific business requirements and error handling strategies. It’s just a way how we can access from DLQ.

Thank you for reading! I hope this article provides valuable insights to help you efficiently handle Dead Letter Queues in Azure Functions. Your feedback is essential, so please share your thoughts and experiences through claps or comments.

Keep Learning :)