Book Image

Mastering Spring Cloud

By : Piotr Mińkowski
Book Image

Mastering Spring Cloud

By: Piotr Mińkowski

Overview of this book

Developing, deploying, and operating cloud applications should be as easy as local applications. This should be the governing principle behind any cloud platform, library, or tool. Spring Cloud–an open-source library–makes it easy to develop JVM applications for the cloud. In this book, you will be introduced to Spring Cloud and will master its features from the application developer's point of view. This book begins by introducing you to microservices for Spring and the available feature set in Spring Cloud. You will learn to configure the Spring Cloud server and run the Eureka server to enable service registration and discovery. Then you will learn about techniques related to load balancing and circuit breaking and utilize all features of the Feign client. The book now delves into advanced topics where you will learn to implement distributed tracing solutions for Spring Cloud and build message-driven microservice architectures. Before running an application on Docker container s, you will master testing and securing techniques with Spring Cloud.
Table of Contents (22 chapters)
Title Page
Copyright and Credits
Packt Upsell

Replication and high availability

We have already discussed some useful Eureka settings, but until now we have analyzed only a system with a single service discovery server. Such a configuration is valid, but only in development mode. For production mode, we would like to have at least two discovery servers running in case one of them fails or a network problem occurs. Eureka is by definition built for availability and resiliency, two primary pillars of development at Netflix. But it does not provide standard clustering mechanisms such as leadership election or automatically joining to the cluster. It is based on the peer-to-peer replication model. It means that all of the servers replicate data and send heartbeats to all of the peers, which are set in configuration for the current server node. Such an algorithm is simple and effective for containing data, but it also has some drawbacks. It limits scalability, because every node has to withstand the entire write load on the server.