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Spring Boot 3.0 Cookbook

You're reading from   Spring Boot 3.0 Cookbook Proven recipes for building modern and robust Java web applications with Spring Boot

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Product type Paperback
Published in Jul 2024
Publisher Packt
ISBN-13 9781835089491
Length 426 pages
Edition 1st Edition
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Author (1):
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Mr. Felip Miguel Puig Mr. Felip Miguel Puig
Author Profile Icon Mr. Felip Miguel Puig
Mr. Felip Miguel Puig
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Table of Contents (16) Chapters Close

Preface 1. Part 1:Web Applications and Microservices FREE CHAPTER
2. Chapter 1: Building RESTful APIs 3. Chapter 2: Securing Spring Boot Applications with OAuth2 4. Chapter 3: Observability, Monitoring, and Application Management 5. Chapter 4: Spring Cloud 6. Part 2: Database Technologies
7. Chapter 5: Data Persistence and Relational Database Integration with Spring Data 8. Chapter 6: Data Persistence and NoSQL Database Integration with Spring Data 9. Part 3: Application Optimization
10. Chapter 7: Finding Bottlenecks and Optimizing Your Application 11. Chapter 8: Spring Reactive and Spring Cloud Stream 12. Part 4: Upgrading to Spring Boot 3 from Previous Versions
13. Chapter 9: Upgrading from Spring Boot 2.x to Spring Boot 3.0 14. Index 15. Other Books You May Enjoy

Spring Reactive and Spring Cloud Stream

A different approach to applications may be necessary in high concurrency scenarios, with resource-intensive operations such as Input/Output (I/O)-bounded tasks that require low latency and responsiveness. In this chapter, we’ll learn about two Spring Boot projects that address such a scenario.

Spring Reactive is Spring’s response to reactive processing scenarios. Reactive processing is a paradigm that allows developers to build non-blocking, asynchronous applications that can handle backpressure. Non-blocking means that when an application waits for an external resource to respond, for instance, when calling an external web service or database, the application doesn’t block the processing thread. Instead, it reuses the processing threads to handle new requests. Backpressure is a mechanism for handling situations where a downstream component cannot keep up with the rate of data production from an upstream component. For...

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