eBook: Download Guerrilla Capacity Planning Tactical Applications ePub (KINDLE, PDF, MOBI) + Audio Version

  • File Size: 9140 KB
  • Print Length: 253 pages
  • Publisher: Springer; 2007 edition (January 17, 2007)
  • Publication Date: January 17, 2007
  • Language: English

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An excellent book on pragmatic techniques to do performance analysis modeling and capacity planning. A high level00 developer or from the procedures domain and you care about application performance and scale the this is a must read. The writer is brilliant., Neil has done a great job of defining the keys to measuring capacity requirements and techniques for getting this done when time resources are restricted., With Wall Street analysts drives the planning horizon, Management prefers getting a sense of direction quickly and repeatedly, as opposed to belated precise readings of compass bearing. It really is in this agile and opportunistic nature and philosophy that Doctor. Gunther introduces Excel, linear regression, and 2 variable scalability models into the performance analysts' tool upper body.

Excel is ubiquitous. It is also easy to use. Use it. If there is sufficient time, better tools such as R or Mathematica can be used to cross-check Excel results. Similarly, linear regression is another tool in the agile performance analysts' tool chest.

Two chapters I use not seen presented in other places are the virtualization spectrum and effective demand. Inside a prior job, having virtualization spectrum chapter available to me would have save me much grief with an workload manager. The effective demand makes another useful capacity project tool to keep handy.

The best part is Doctor. Gunther's 2 parameter common scalability model. It can be immediately used to frame your load tests results to project application scalability. This alone is worth the price of the guide and admission to his classes.

Conjecture 4. one on page 65 on 2 parameters are necessary and sufficient for scalability model based on rational functions are an interesting open up questions. Given that the denominator is a quadratic equation with c = 1, we ought to be able to argue that it reacts like a parabola, other than with c = one, we won't get into singularity/infinity. For more information, please see Dr. Gunther's blog at

[... ], Very first of all, this guide was worth the money I spent on it. I came away from reading this article book with a clear comprehension of the differences between speed and scale, and with a system for modelling the scalability of systems in general.

However... really all of this value was at the first quarter of the guide. I read on and read on looking for further conceptual gems but they weren't found.

I suppose that books are "meant" to be at least a particular length, but this one could have been much shorter and more concise., Very legible coverage of Capacity Organizing and Performance Management. Does not presume any previous knowledge, but doesn't talk down either. Several good chapters referring to queueing theory.
A great useful handbook., Doctor Neil Gunther has undertaken an important work, those of teaching to IT professionals the basics of measuring and modeling the scalability of parallel computer systems. The model he develops in his guide is a useful starting point; however, it fails to provide a completely general basis for modeling the behaviour of the broad variety of current seite an seite computer systems.

The "universal scalability law" that he describes in section 4. 4, and for which he provides figure 4. 8 and equation 4. 31, extends Amdahl's Legislation via the addition of a "coherency" term that models effects such as data exchange between seite an seite processes. And although Doctor Gunther suggests that this coherency term ought to grow linearly with the number of parallel procedures, and hence should seem as a quadratic term in equation 4. 31, this coherency term depends upon the particular communication architecture of the computer system and can grow non-linearly, for example, as log to the base two of the quantity of processes.

This logarithmic growth law may occur because one processor may well not talk directly with all other processors. Instead, one cpu may send information to two other processors, and each of those two processors may send information to two more processors, and so on. Therefore, in order to model the communication that occurs in this communication cascade, the quadratic n(n-1) coherency term in formula 4. 31 should be replaced by an n*log(n) term.

Moreover, performance data that are obtained from current parallel computer systems do not at all times conform to Dr. Gunther's "universal" scalability "law" under other conditions. For example, a large volume of data that exceeds the capability of the total refuge memory when distributed across a few processors may well fit into total refuge memory when distributed across a larger quantity of processors. Under these conditions, the scalability for the bigger quantity of processors appears to grow "super-linearly" relative to the scalability of a few processors. However, Doctor Guther's model specifically disallows this "super-linear" scaling that is commonly observed. Thus, although Dr. Gunther's guide is a useful intro to the subject of measuring and modeling the behavior of parallel computer architectures, his universal scalability law really should not be considered to be universal., I've browse the other reviews and they seem to ignore the "Guerrilla" concept. The reality that scientific analysis is ignored and selections made on perceived knowledge in many companies for me is the key to the book. Excel is a good way to get the performance point across even with precision errors. Getting management buy in is 00% of the process. GCP makes that argument simple. Study this book and obtain the word out. Performance is not linear!

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Guerrilla Capacity Planning Tactical Applications
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