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4.5/5 Best read with: A JMH project open in your IDE and a multi-core machine with perf or async-profiler installed.
Target Audience: Intermediate to Expert Java developers, performance engineers, architects, and SREs who want data-driven insights rather than folklore. Summary Unlike typical Java performance books (e.g., Java Performance by Scott Oaks), this title emphasizes a quantitative, measurement-first methodology . It avoids blanket advice like “use StringBuilder everywhere” or “avoid streams for performance.” Instead, it builds a framework for forming hypotheses, designing microbenchmarks (using JMH), interpreting statistics, and understanding how JVM behaviors scale with load, data size, and concurrency.
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4.5/5 Best read with: A JMH project open in your IDE and a multi-core machine with perf or async-profiler installed.
Target Audience: Intermediate to Expert Java developers, performance engineers, architects, and SREs who want data-driven insights rather than folklore. Summary Unlike typical Java performance books (e.g., Java Performance by Scott Oaks), this title emphasizes a quantitative, measurement-first methodology . It avoids blanket advice like “use StringBuilder everywhere” or “avoid streams for performance.” Instead, it builds a framework for forming hypotheses, designing microbenchmarks (using JMH), interpreting statistics, and understanding how JVM behaviors scale with load, data size, and concurrency. Java Performance And Scalability A Quantitative Approach