Book Image

Building Microservices with Spring

By : Dinesh Rajput, Rajesh R V
Book Image

Building Microservices with Spring

By: Dinesh Rajput, Rajesh R V

Overview of this book

Getting Started with Spring Microservices begins with an overview of the Spring Framework 5.0, its design patterns, and its guidelines that enable you to implement responsive microservices at scale. You will learn how to use GoF patterns in application design. You will understand the dependency injection pattern, which is the main principle behind the decoupling process of the Spring Framework and makes it easier to manage your code. Then, you will learn how to use proxy patterns in aspect-oriented programming and remoting. Moving on, you will understand the JDBC template patterns and their use in abstracting database access. After understanding the basics, you will move on to more advanced topics, such as reactive streams and concurrency. Written to the latest specifications of Spring that focuses on Reactive Programming, the Learning Path teaches you how to build modern, internet-scale Java applications in no time. Next, you will understand how Spring Boot is used to deploying serverless autonomous services by removing the need to have a heavyweight application server. You’ll also explore ways to deploy your microservices to Docker and managing them with Mesos. By the end of this Learning Path, you will have the clarity and confidence for implementing microservices using Spring Framework. This Learning Path includes content from the following Packt products: • Spring 5 Microservices by Rajesh R V • Spring 5 Design Patterns by Dinesh Rajput
Table of Contents (22 chapters)
Title Page
Copyright
About Packt
Contributors
Preface
Index

Back-pressure


A reactive application is never given up in overload conditions. Back-pressure is a key aspect of a reactive application. It is a mechanism to ensure that the reactive application doesn't overwhelm the consumers. It tests aspects for the reactive application. It tests the system response gracefully under any load.

The back-pressure mechanism ensures that the system is resilient under load. In a back-pressure condition, the system makes itself scalable by applying other resources to help distribute the load.

Until now, we have seen the reactive pattern principles; these are mandatory to make a system responsive in the blue sky or grey sky. Let's see, in the upcoming section how Spring 5 implements reactive programming.