Queue Based Report Generation in Spring Boot with Message Brokers

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Direct asynchronous execution can handle many reporting needs, but larger applications or distributed systems often require more than in-process background work. A message broker can manage the distribution of report jobs in a way that allows more scaling flexibility and better reliability. Instead of processing reports in the same application that receives the request, the work is sent to dedicated workers through a queue. This lets the processing layer scale independently, while the web layer continues to serve incoming requests without being slowed by heavy jobs.

This is a companion article that builds on another guide covering direct async processing. The concepts here expand on that foundation with a queue-driven model for report generation, offering an alternate architecture for solving the same problem space. If you haven’t yet, check out the original here:

On Demand Report Generation in Spring Boot with Async Processing

Why Use a Message Broker for Reports

In the main article, report generation happened through @Async methods running in a dedicated thread pool. This keeps the application responsive, but the work still happens inside the same service process. If the application receives a surge of report requests, the thread pool can be saturated, causing delays for other asynchronous work. In this article we will use RabbitMQ between the web tier and the report generation logic. Kafka needs different client libraries and configuration. When a report request comes in, the details are routed to an exchange and land on a queue through a binding. Make sure to declare a Queue, Exchange, and Binding as Spring beans so Spring AMQP creates them at startup. Publishing to a missing exchange will fail, and messages sent to an exchange without any bound queues are dropped. This queue can then be processed by one or more worker services dedicated entirely to building reports.