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
Contributors
Preface
Index

Using Apache Kafka


I have mentioned Apache Kafka a couple of times when discussing Spring Cloud integration with message brokers. However, until now, we haven't run any samples based on that platform. The fact is that RabbitMQ tends to be the preferred choice when working with Spring Cloud projects, but Kafka is also worthy of our attention. One of its advantages over RabbitMQ is native support for partitioning, which is one of the most important features of Spring Cloud Stream.

Kafka is not a typical message broker. It is rather a distributed streaming platform. Its main feature is to allow you to publish and subscribe to streams of records. It is especially useful for real-time streaming applications that transform or react to streams of data. It is usually run as a cluster consisting of one or more servers, and stores streams of records in topics.

Running Kafka

Unfortunately, there is no official Docker image with Apache Kafka. However, we may use one that is unofficial, for example, that...