You're reading from Java Concurrency and Parallelism Master advanced Java techniques for cloud-based applications through concurrency and parallelism

Product type Paperback

Published in Aug 2024

Publisher Packt

ISBN-13 9781805129264

Length 496 pages

Edition 1st Edition

Languages

Java

Tools

Boost

Concepts

Application Development

Author (1):

Jay Wang

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Table of Contents (20) Chapters

Preface

1. Part 1: Foundations of Java Concurrency and Parallelism in Cloud Computing

2. Chapter 1: Concurrency, Parallelism, and the Cloud: Navigating the Cloud-Native Landscape FREE CHAPTER

3. Chapter 2: Introduction to Java’s Concurrency Foundations: Threads, Processes, and Beyond

4. Chapter 3: Mastering Parallelism in Java

5. Chapter 4: Java Concurrency Utilities and Testing in the Cloud Era

6. Chapter 5: Mastering Concurrency Patterns in Cloud Computing

7. Part 2: Java's Concurrency in Specialized Domains

8. Chapter 6: Java and Big Data – a Collaborative Odyssey

9. Chapter 7: Concurrency in Java for Machine Learning

10. Chapter 8: Microservices in the Cloud and Java’s Concurrency

11. Chapter 9: Serverless Computing and Java’s Concurrent Capabilities

12. Part 3: Mastering Concurrency in the Cloud – The Final Frontier

13. Chapter 10: Synchronizing Java’s Concurrency with Cloud Auto-Scaling Dynamics

14. Chapter 11: Advanced Java Concurrency Practices in Cloud Computing

15. Chapter 12: The Horizon Ahead

16. Index

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Appendix A: Setting up a Cloud-Native Java Environment

1. Appendix B: Resources and Further Reading

Specialized monitoring for Java concurrency in the cloud

Monitoring concurrent operations in cloud environments is crucial for several key reasons. Performance optimization stands at the forefront, as it allows developers to identify bottlenecks and inefficiencies in parallel execution. Effective monitoring ensures efficient resource management across distributed systems, a critical aspect of cloud computing. It also plays a vital role in error detection, enabling quick identification and diagnosis of issues related to race conditions or deadlocks. Furthermore, monitoring provides valuable scalability insights, helping teams understand how applications perform under varying loads, which in turn informs scaling decisions. Lastly, it contributes to cost control by optimizing resource usage, an essential factor in managing cloud computing expenses effectively.