FIFO Messaging with Azure Service Bus and Spring Boot

Introduction

Azure Service Bus is a fully managed message broker that facilitates reliable communication between distributed applications. For applications that require messages to be processed in a specific order, such as ensuring a First-In-First-Out (FIFO) sequence, sessions in Azure Service Bus provide an effective mechanism for message processing.

In the context of a Spring Boot application, leveraging sessions on an Azure Service Bus topic ensures that messages with the same Session ID are handled in the correct order by a single consumer at a time. This solution is particularly useful when handling high-throughput messaging scenarios while maintaining message order.

This guide outlines how to configure a Spring Boot application to consume messages from Azure Service Bus in FIFO order, ensuring reliability and scalability by using sessions without the need for complex infrastructure.

In practice

For a Spring Boot application deployed on multiple instances to consume messages from an Azure Service Bus topic in FIFO order, you can use sessions on the topic and configure the application to manage sessions in a coordinated between the authorities. Here's how to do it:

1. Enable Sessions on the Azure Service Bus Topic

• Make sure the Azure Service Bus topic and subscription are configured to use sessions.
• When sending messages, set a Session ID on each message to ensure that all messages with the same Session ID will be processed in order of arrival by only one consumer at a time.

2. Use the Azure SDK to Manage Sessions in Spring Boot

Azure provides libraries for Java that allow messages to be consumed with sessions in an orderly manner. Here is one approach:

Add Azure Service Bus Dependency

Add the dependency for Azure Service Bus in your Spring Boot project (in pom.xml for Maven):

<dependency>
    <groupId>com.azure</groupId>
    <artifactId>azure-messaging-servicebus</artifactId>
    <version>7.5.0</version> <!-- check for the last version -->
</dependency>

Configure the Service Bus in the Application

Configure the application to connect to the Azure Service Bus topic. Here is a basic configuration:

import com.azure.messaging.servicebus.*;

@Service
public class AzureServiceBusConsumer {

    private final String connectionString = "Endpoint=sb://<your-service-bus>.servicebus.windows.net/;SharedAccessKeyName=<key-name>;SharedAccessKey=<key>";
    private final String topicName = "<your-topic>";
    private final String subscriptionName = "<your-subscription>";

    public void startSessionProcessor() {
        ServiceBusClientBuilder clientBuilder = new ServiceBusClientBuilder()
                .connectionString(connectionString);

        ServiceBusProcessorClient processorClient = clientBuilder
                .sessionProcessor() // Using session mode
                .topicName(topicName)
                .subscriptionName(subscriptionName)
                .processMessage(this::processMessage)
                .processError(this::processError)
                .buildProcessorClient();

        // Start session processing in asynchronous mode
        processorClient.start();
    }

    private void processMessage(ServiceBusReceivedMessageContext context) {
        ServiceBusReceivedMessage message = context.getMessage();
        System.out.printf("Processing message from session: %s. Contents: %s%n",
                message.getSessionId(), message.getBody());

        // Process the message here, respecting the order of arrival in the session
        context.complete(); // Mark the message as processed
    }

    private void processError(ServiceBusErrorContext context) {
        System.err.printf("Error occurred while processing: %s%n", context.getException().getMessage());
    }
}

Ensure Unique Consumption per Session

Using sessionProcessor() ensures that each session is consumed by only one instance at a time, and messages in a session are always processed in FIFO order, regardless of the number of instances.

3. Concurrency Management between EC2 Instances

When multiple EC2 instances of the application are connected to the topic:

• Azure Service Bus dynamically assigns sessions to available consumers.
• Each Spring Boot instance receives messages one session at a time, and Azure Service Bus ensures that an active session will not be assigned to multiple consumers simultaneously.
• This allows for automatic scaling, with each instance supporting different sessions in parallel.

4. Deployment and Resilience

Deploy the Spring Boot application on your EC2 instances with identical Service Bus configurations, so they can dynamically manage sessions. If an instance goes down, Azure Service Bus will automatically reassign the waiting session to another connected EC2 instance.

5. Launch Example in Spring Boot

Launch the consumer when your Spring Boot application starts, using @PostConstruct to start in-session consumption:

import javax.annotation.PostConstruct;
import org.springframework.stereotype.Service;

@Service
public class AzureServiceBusConsumer {

    // ... (configuration and previous code)

    @PostConstruct
    public void init() {
        startSessionProcessor();
    }
}

Conclusion

In conclusion, integrating Azure Service Bus with a Spring Boot application for FIFO message processing can be effectively achieved by utilizing sessions. By enabling sessions on the Azure Service Bus topic and associating messages with a specific Session ID, you ensure that messages are processed in the exact order they arrive, within each session.

Using the Azure SDK for Java, the Spring Boot application can be configured to consume messages in a session-based manner, guaranteeing that each session is processed by a single consumer at a time. This eliminates the risk of message reordering, even in a multi-threaded environment, ensuring reliable and ordered processing.

This approach offers a scalable and resilient solution, ensuring that the application processes messages in strict FIFO order while maintaining efficiency and flexibility in managing distributed workloads.