The previous chapters taught us how a reactive programming paradigm can become a pleasure to work with when using Reactor 3. So far, we have learned how to build a reactive web application using Spring WebFlux and Spring Data Reactive. This robust combination makes it possible to build an application that is capable of handling a high load while also providing the efficient resource utilization, a low memory footprint, low latency, and high throughput.

However, this is not the end of the possibilities that come with the Spring ecosystem. In this chapter, we are going to learn how to improve our application using the features offered by the Spring Cloud ecosystem as well as learning how to build a complete reactive system using Spring Cloud Streams. In addition, we are going to see what the RSocket library is and how it can help us develop fast streaming systems. Finally, this chapter also covers the Spring Cloud Function module, which simplifies the construction of a cloud-native reactive system based on reactive programming and backpressure support.

In this chapter, we will cover the following topics:

• The role of message brokers in reactive systems
• The role of Spring Cloud Streams in reactive systems with Spring Framework
• Serverless reactive systems with Spring Cloud Function
• RSocket as an application protocol for asynchronous, low-latency message passing