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Java Concurrency and Parallelism

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

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Product type Paperback
Published in Aug 2024
Publisher Packt
ISBN-13 9781805129264
Length 496 pages
Edition 1st Edition
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Author (1):
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Jay Wang Jay Wang
Author Profile Icon Jay Wang
Jay Wang
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Table of Contents (20) Chapters Close

Preface 1. Part 1: Foundations of Java Concurrency and Parallelism in Cloud Computing FREE CHAPTER
2. Chapter 1: Concurrency, Parallelism, and the Cloud: Navigating the Cloud-Native Landscape 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 17. Other Books You May Enjoy Appendix A: Setting up a Cloud-Native Java Environment 1. Appendix B: Resources and Further Reading

Service mesh and APM – your cloud performance powerhouse

Imagine your cloud application as a bustling marketplace, with microservices such as vendors conducting transactions. Without a conductor, things get chaotic. Service mesh, such as Istio and Linkerd, ensures each microservice plays its part flawlessly:

  • Transparent observability: See how data flows between services, identify bottlenecks, and debug issues, all without modifying your code
  • Traffic management: Route requests efficiently, avoiding overloads and ensuring smooth performance even during peak traffic
  • Consistent policy enforcement: Set rules (e.g., retry policies, rate limits) globally for all services, simplifying management and guaranteeing predictable behavior

Now, imagine a skilled musician analyzing the marketplace soundscape. That’s what APM solutions such as Dynatrace, New Relic, and Elastic APM do:

  • Observability beyond monitoring: Go beyond basic metrics to correlate...
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