Gain insights into building Reactive Web Applications with Spring Boot 2 and Spring WebFlux, from database integration to front-end. Explore Reactive vs MVC, performance, and deployment with Docker.   


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This course is your guide to using Spring Boot 2 and Spring WebFlux to create Reactive Web Applications. 

You will learn how to build a full-reactive system from the database (MongoDB reactive) to the front-end (Angular), using a Reactive programming strategy leveraged by Spring WebFlux, with the simplicity offered by Spring Boot 2. 

Beyond that though, you will be able to compare the Spring WebFlux with the standard MVC approach as well, covering the main aspects such as simplicity, performance, user experience, and more.

The last part of the course ties it all up by teaching you to run the application using Docker compose. By the end of this course, you will have a great new skill for your resume and you’ll be able to build your own projects using the full Reactive stack.

Full Reactive Stack: Spring Boot 2 & Spring WebFlux

## Overview

Project Reactor is a framework built by Pivotal and powered by Spring. It implements reactive programming patterns and, more specifically, the Reactive Streams specification.

If you’re familiar with Java 8 *Streams*, you’ll quickly find many similarities between a Stream and a **Flux** (or its single-element version, **Mono**). The main characteristics that differentiate Fluxes and Monos from the Stream API are that the first two follow a *publisher-subscriber* pattern and implement #key# backpressure: The ability for the consumer to signal the producer that the rate of emission is too high. #key#.

### Publish-subscriber pattern and backpressure

For instance, if you declare a Flux that takes elements from a database, maps them by applying an operation, and filters them according to some random criteria, then _nothing happens_. It will do all these operations _only when a subscriber subscribes to the Flux_. Furthermore, the items flow through the processing logic only when the subscriber is ready to consume more elements. This is the **backpressure** concept we mentioned earlier in this course.


# Overview

Project Reactor is a framework built by Pivotal and powered by Spring. It implements reactive programming patterns and, more specifically, the Reactive Streams specification.

If you’re familiar with Java 8 *Streams*, you’ll quickly find many similarities between a Stream and a **Flux** (or its single-element version, **Mono**). The main characteristics that differentiate Fluxes and Monos from the Stream API are that the first two follow a *publisher-subscriber* pattern and implement #key# backpressure: The ability for the consumer to signal the producer that the rate of emission is too high. #key#.

## Publish-subscriber pattern and backpressure

For instance, if you declare a Flux that takes elements from a database, maps them by applying an operation, and filters them according to some random criteria, then _nothing happens_. It will do all these operations _only when a subscriber subscribes to the Flux_. Furthermore, the items flow through the processing logic only when the subscriber is ready to consume more elements. This is the **backpressure** concept we mentioned earlier in this course.


Learn about the main features of Project Reactor.

Reactive Web

Full Reactive Stack Backend

Connecting Angular With the WebFlux Backend

Conclusion

Appendix

Project Reactor: Main Features

Overview

Publish-subscriber pattern and backpressure