Reactive Web Apps with Spring WebFlux

WebFlux is a web framework based on top of a reactive stack.


In this context, reactive refers to design guidelines on providing resilient, responsive, scalable and message driven applications. Reactive Manifesto is an important document about this topic.

WebFlux is built on reactive-streams specification, which only has components like Subscriber, Publisher, Subscription and Processor. Instead of building their custom implementation based on this specification, WebFlux uses the ProjectReactor library. Project Reactor is an incredibly well implementation of reactive streams with Mono and Flux as their publishers.

WebMVC and WebFlux

While WebFlux is a new and more modern way of creating web applications, it is not necessarily faster or easier to use. It is important to note that WebMVC also has a non-blocking io support. However, filters and route functions are not completely non-blocking.


The first things we need to realize with WebFlux is why blocking calls is an undesirable thing. One of the most important benefits of WebFlux is that it uses a low number of threads compared to WebMVC. Using a low number of threads can be better because creating each thread has a cost of memory and each context switch wastes some time.

With WebMVC, when we make a database call, the thread can wait until it gets a response because there are usually hundreds of them to handle concurrent requests.

With WebFlux, we assign a callback function which would work when the database call is finished. The worker thread would continue consuming tasks from the event-loop. If we design our system correctly, this is a really efficient use of resources. Although, using a low number of threads mean each one of them is more precious so any blocking call could result in a huge performance issue.

This is why we should be comfortable working with Publishers and Subscribers in a functional manner.

public Mono<Record> save(Record record) {
            .doOnError(e -> LOG.error("Something went wrong", e);

Calling the save method with a Record is not enough to save it to the database. If we were to use project reactor alone, we would need to subscribe to Publishers manually.

        i -> System.out.println(i), // on next item
        error -> System.err.println("Error " + error), // on error
        () -> System.out.println("Done") // on complete

However, we should be returning Mono/Flux in our Controllers anyway. So we don’t need to worry about schedulers or subscriptions and WebFlux should handle subscriptions to our publishers.

public Mono<Record> save(@Valid @RequestBody Record record) {

would actually save the item to the database.

There might be some instances where we want to run some functions asynchronously. We should use schedulers in these cases.


parallel(): Optimized for fast Runnable non-blocking executions single(): Optimized for low-latency Runnable one-off executions elastic(): Optimized for longer executions, an alternative for blocking tasks where the number of active tasks (and threads) can grow indefinitely boundedElastic(): Optimized for longer executions, an alternative for blocking tasks where the number of active tasks ( and threads) is capped immediate(): to immediately run submitted Runnable instead of scheduling them (somewhat of a no-op or “null object” Scheduler)


Spring already has a strong suite of libraries supporting reactive web apps with non-blocking functions. Some libraries I had the chance to use are:

  • spring security
  • spring actuator
  • micrometer
  • r2dbc
  • reactive redis
  • spring data
  • thymeleaf
  • spring cloud sleuth
  • webclient

Spring Cloud Sleuth

Using Thread Local to carry contextual data is easy to accomplish in WebMVC applications because of the thread-per-request approach.

Carrying contextual data is useful when it is difficult to carry a parameter like an id from WebFilters all the way down to the layer where we make database calls. For an example, we can use MDC from log4j to append correlationIds to all logs from a request.

Implementing the same thing in WebFlux is a little more difficult because a low number of threads process callbacks from different requests concurrently. There is still a way to carry contextual data in WebFlux through subscriber context. We can implement it ourselves manually, but Sleuth not only makes context propagation easier, it also adds tracing variables to the context in opentracing format if we want.


WebClient is a replacement for RestTemplate in the reactive world. It is a strong, fast and modern client which can be used in non-reactive java apps as well. It is really easy to implement retry policies, request timeouts, error handling and logging after getting used to it.

WebFilters and WebFlux.fn

WebFilters are the replacement to Filters from WebMVC. They are pretty similar, but they work in a non-blocking way.

We can still use traditional Controllers with annotations like @PostMapping or @GetMapping but there is a functional alternative in WebFlux named WebFlux.fn. HandlerFunction and RouterFunction are interfaces which we can use to create request handlers.

HandlerFunction<ServerResponse> helloWorld = 
    request -> ServerResponse.ok().bodyValue("Hello World");
RouterFunction<ServerResponse> route = route()
    .path("/person", builder -> builder
        .GET("/{id}", accept(APPLICATION_JSON), handler::getPerson)
        .GET(accept(APPLICATION_JSON), handler::listPeople)
        .POST("/person", handler::createPerson))

Lessons Learned

Built-in reliability functions

Functions like timeout, retry, log and doOnError are incredibly useful. In fact, not using doOnError might mean missing errors in some cases.


BlockHound is a java agent which detects blocking function calls in our Project Reactor apps. It helps by telling us the line blocking takes place. Since blocking can cause huge performance issues on production, preventing them is a big issue.

Publisher and Subscriber Functions

Get comfortable with functions on Mono and Flux. Functions like onErrorResume, onErrorReturn, flatmap, merge or Mono.defer() may look like optional at first. There are many use cases for them even in the most basic applications.

Spring MVC dependencies

Make sure you do not have spring-boot-starter-web in your classpath, otherwise your application might not be running in reactive mode. From WebFlux Documents

Adding both spring-boot-starter-web and spring-boot-starter-webflux modules in your application results in Spring Boot auto-configuring Spring MVC, not WebFlux. This behavior has been chosen because many Spring developers add spring-boot-starter-webflux to their Spring MVC application to use the reactive WebClient. You can still enforce your choice by setting the chosen application type to SpringApplication.setWebApplicationType(WebApplicationType.REACTIVE).