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The book is broken into six parts consisting of 36 chapters and ten appendices. Part I is an overview of performance evaluation. I liked the chapter on common mistakes and how to avoid them, and the guidelines for selecting techniques and metrics.
Measurement techniques and tools are the focus of Part II. the eight chapters in this part address the full spectrum, including workload types, characterization techniques, capacity planning and benchmarking, and data presentation. Most of the chapters are generic enough to be timeless. The chapters covering execution monitors and accounting logs are showing their age, but the concepts are still valid. I especially liked the chapters about data presentation and ratios.
Part III is a refresher in statistics and probability, and can safely be skipped if your knowledge and skills are fresh. Part IV delves into experimental design and analysis, while Part V covers simulations. The remaining six chapters of the book, Part VI, are devoted to queuing models.
Note that although the math is clearly explained you need college level skills in order to fully comprehend the techniques presented. I recommend investing in MathCAD or a similar program to make it easy to work the exercises that end each chapter.
This book is one of the handful that will be on your bookshelf for years to come. It's probably one of the most frequently referenced works in the performance analysis, resource management and capacity planning knowledge domains. Because it has well designed exercises at the end of each chapter it's also well suited as an advanced college level text. In my opinion it's essential reading for performance and capacity analysts, and provides an excellent foundation for more specialized books, such as those by Menasce and Almeida, that address topics such as e-commerce performance, web services, etc.
He outlines and elaborates a methodical, straightforward approach to performance analysis and provides excellent sections on what to do, not do, and how to validate or refute the analyses of others.
Extensive examples with solutions and enough equations to let you easily implement the analysis portions in code (or a spreadsheet if need be).
If you are doing any kind of performance analysis, whether it is for computer systems or not, you should get a copy.
The only reason I didnt give it 5 stars is a very small number of the example answers have typos or rounding errors. Be sure to get the errata list from the website.
This book has been written assuming a novice reader. Several parts of the book have to re-read to really understand what the author is trying to convey, but trust me you will really appreciate it.
I suggest reading the following parts of the book(in order):
Part I (whole)
Part II (4, 5, 6, browse {7,8}, 9, 10 ) 10 is cool stuff..impress your peers with this
Part III (whole) read, re-read, re-read till you have digested every line..worth it really!!!!
Part IV (whole) read, re-read, re-read till you have digested every line..worth it really!!!!
Part V : You can skip this if you are not into simulation.
Part VI : Not really that easy to follow. I suggest Gunter's book for this.
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