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Microservices with Spring Boot 3 and Spring Cloud, Third Edition - Third Edition

You're reading from  Microservices with Spring Boot 3 and Spring Cloud, Third Edition - Third Edition

Product type Book
Published in Aug 2023
Publisher Packt
ISBN-13 9781805128694
Pages 706 pages
Edition 3rd Edition
Languages
Author (1):
Magnus Larsson Magnus Larsson
Profile icon Magnus Larsson

Table of Contents (26) Chapters

Preface 1. Introduction to Microservices 2. Introduction to Spring Boot 3. Creating a Set of Cooperating Microservices 4. Deploying Our Microservices Using Docker 5. Adding an API Description Using OpenAPI 6. Adding Persistence 7. Developing Reactive Microservices 8. Introduction to Spring Cloud 9. Adding Service Discovery Using Netflix Eureka 10. Using Spring Cloud Gateway to Hide Microservices behind an Edge Server 11. Securing Access to APIs 12. Centralized Configuration 13. Improving Resilience Using Resilience4j 14. Understanding Distributed Tracing 15. Introduction to Kubernetes 16. Deploying Our Microservices to Kubernetes 17. Implementing Kubernetes Features to Simplify the System Landscape 18. Using a Service Mesh to Improve Observability and Management 19. Centralized Logging with the EFK Stack 20. Monitoring Microservices 21. Installation Instructions for macOS 22. Installation Instructions for Microsoft Windows with WSL 2 and Ubuntu 23. Native-Complied Java Microservices 24. Other Books You May Enjoy
25. Index

Summary

In this chapter, we have seen how we can develop reactive microservices!Using Spring WebFlux and Spring WebClient, we can develop non-blocking synchronous APIs that can handle incoming HTTP requests and send outgoing HTTP requests without blocking any threads. Using Spring Data's reactive support for MongoDB, we can also access MongoDB databases in a non-blocking way, that is, without blocking any threads while waiting for responses from the database. Spring WebFlux, Spring WebClient, and Spring Data rely on Project Reactor to provide their reactive and non-blocking features. When we must use blocking code, for example, when using Spring Data for JPA, we can encapsulate the processing of the blocking code by scheduling the processing of it in a dedicated thread pool.We have also seen how Spring Data Stream can be used to develop event-driven asynchronous services that work on both RabbitMQ and Kafka as messaging systems without requiring any changes in the code. By doing...

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