Use this in-depth guide to correctly design benchmarks, measure key performance metrics of .NET applications, and analyze results. This book presents dozens of case studies to help you understand complicated benchmarking topics. You will avoid common pitfalls, control the accuracy of your measurements, and improve performance of your software.
I have been a programmer for a long time but never really did a deep dive into this topic until now. Admittedly, I felt the book verbose, but I will cut the author some slack because this topic is so specialized. He is clearly an expert in this subject matter. I am eager to use some of this. The GC discussion was great. It is refreshing to see a win for Apress—some of their books have been subpar lately. I recommend this book for anyone wanting to learn more about this topic.
on of these rare technical books that would teach you transferable skills (how to benchmark, read benchmarking stats, measure performance, understand h/w (CPU, memory, only, but it's a good start) impact on your code) and at the same seriously geeks-out; clearly written by a passionate and expert in the domain (don't worry despite Andrey Akinshin being one of main guys behind BenchmarkDotNet the book doesn't try to sell it, instead you would benefit from years of his experience working in benchmarking, performance analysis space); well worth time of a serious .net developer (with a few chapters being technology stack agnostic, hence worth scanning even if you are coming from C++, Java, etc).
Between 4 and 5 stars. Disclaimer: I'm not the target audience for this book.
If you're .net developer and just getting into performance engineering - this is THE book for you. If you're not .net developer - maybe 60% of the book is for you. If you've done fair share of performance engineering in your life - you can skip this one.
The book not super deep and tries to scratch many surfaces. If you don't know much about .NET internals and hardware and don't know understand the basics of performance engineering - this is a great package, otherwise you'll have to skim quite a bit. Some chapters are more watery than others.
Fundamentals of performance measurements and statistics does a great job - very easy on math while covering the most important aspects: how to run experiments and collect results in noise environments, how to compare experiment results, very small theoretical background and very practical recipes.
But i think for JVM crowd I would still recommend reading "Naked Statistics" + "Java Performance: In-Depth Advice for Tuning and Programming Java 8, 11, and Beyond" instead of this one.