优化云原生Java：提高JVM应用程序性能的实用技术（真价/零售EPUB）
Performance tuning is an experimental science, but that doesn't mean engineers should resort to guesswork and folklore to get the job done. Yet that's often the case. With this practical book, intermediate to advanced Java technologists working with complex platforms will learn how to tune Java cloud applications for performance using a quantitative, verifiable, and repeatable approach.
In response to the ubiquity of cloud computing, this updated edition of Optimizing Cloud Native Java addresses topics that are key to high performance of Java applications in the cloud. Many resources on performance tend to focus on the theory and internals of Java virtual machines, but this book discusses the low-level technical aspects within the context of performance-tuning practicalities and examines a wide range of aspects.
With this book, you will • Learn how Java principles and technology make the best use of modern hardware, operating systems, and cloud stacks • Examine the pitfalls of measuring Java performance numbers and the drawbacks of microbenchmarking • Understand how to package, deploy, operate, and debug Java/JVM applications in modern cloud environments • Apply emerging observability approaches to obtain deep understanding of cloud native applications • Use Java language performance techniques including concurrent and distributed forms
性能调优是一门实验性科学，但这并不意味着工程师应该依靠揣测和传说来完成任务。然而，这种情况往往会发生。凭借这本书，那些在复杂平台上与中高级Java技术专家将学习如何使用量化的、可验证的且可重复的方法为Java云应用程序进行性能调优。
针对云计算的普遍性，《优化云原生Java》这一新版书籍回应了许多关于高性能Java应用程序的关键问题，并讨论了在云计算环境中实际操作的技术细节。许多与性能相关的资源往往聚焦于Java虚拟机的理论和内部结构，但此书则结合实际的性能调优实践探讨了低层次的技术方面，并广泛考察了各种方面。
通过这本书，你可以 • 学习如何利用现代硬件、操作系统和云堆栈来充分发挥Java原则和技术的价值 • 探索测量Java性能数据陷阱以及微基准测试带来的弊端 • 理解如何在现代云计算环境中打包、部署、管理和调试Java/JVM应用程序 • 应用新兴的可观测性方法以获得对云原生应用的深入理解 • 使用包括并发和分布式形式在内的Java语言性能技巧
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