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Guerrilla Capacity Planning: A Tactical Approach to Planning for Highly Scalable Applications and Services [Englisch] [Gebundene Ausgabe]

Neil J. Gunther

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Kurzbeschreibung

14. November 2006 3540261389 978-3540261384 2007

Under today’s shortened fiscal horizons and contracted time-to-market schedules, traditional approaches to capacity planning are seen by management as inflating production schedules. In the face of relentless pressure to get things done faster, this book facilitates rapid forecasting of capacity requirements, based on opportunistic use of available performance data and tools so that management insight is expanded but production schedules are not. The book introduces such concepts as an iterative cycle of improvement called "The Wheel of Capacity Planning," and Virtual Load Testing, which provides a highly cost-effective method for assessing application scalability.


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In these days of shortened fiscal horizons and contracted time-to-market schedules, traditional approaches to capacity planning are often seen by management as tending to inflate their production schedules. Rather than giving up in the face of this kind of relentless pressure to get things done faster, "Guerrilla Capacity Planning" facilitates rapid forecasting of capacity requirements based on the opportunistic use of whatever performance data and tools are available in such a way that management insight is expanded but their schedules are not. A key Guerrilla concept is tactical planning whereby short-range planning questions and projects are brought up in team meetings such that management is compelled to know the answer, and therefore buys into capacity planning without recognizing it as such. Once you have your "foot in the door", capacity planning methods can be refined in an iterative cycle of improvement called "The Wheel of Capacity Planning". Another unique Guerrilla tool is Virtual Load Testing, based on Dr. Gunther's "Universal Law of Computational Scaling", which provides a highly cost-effective method for assessing application scalability.

Über den Autor und weitere Mitwirkende

Neil J. Gunther, M.Sc., Ph.D., SMIEEE, is an internationally recognized IT researcher and computer performance analyst who founded Performance Dynamics Company (www.perfdynamics.com) in 1994. Originally from Melbourne, Australia, he has resided near Silicon Valley in California since 1980. In that time Dr. Gunther has held teaching positions at California State University-Hayward and San Jose University, as well as research and management positions at Xerox PARC, Pyramid/Siemens Technology, and JPL/NASA where he worked on the Voyager and Galileo missions. His "Guerrilla Capacity Planning" classes have been presented at such organizations as America Online (AOL), Boeing, FedEx, Motorola, Nokia, Stanford University, Sun Microsystems and UCLA. In 1996, Dr.

Gunther was awarded Best Technical Paper at the Computer Measurement Group international conference (CMG'96) and at CMG'08 he received the prestigious A.A. Michelson Award---the industry's highest honor for computer performance analysis and capacity planning. Dr. Gunther is also a member of AMS, APS, ACM and SPIE. More details can be found on his Wiki page.


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Amazon.com: 4.7 von 5 Sternen  7 Rezensionen
3 von 3 Kunden fanden die folgende Rezension hilfreich
4.0 von 5 Sternen A useful introduction to the scalability of parallel computing 12. September 2010
Von Photo/Video Gearhead - Veröffentlicht auf Amazon.com
Format:Gebundene Ausgabe
Dr. Neil Gunther has undertaken an important work, that of teaching to IT professionals the basics of measuring and modeling the scalability of parallel computer systems. The model that he develops in his book is a useful starting point; however, this model fails to provide a sufficiently general basis for modeling the behavior of the wide variety of current parallel 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 Law via the addition of a "coherency" term that models effects such as data exchange between parallel processes. And although Dr. Gunther suggests that this coherency term ought to grow linearly with the number of parallel processes, and hence should appear as a quadratic term in equation 4.31, this coherency term depends on the specific communication architecture of the computer system and can grow non-linearly, for example, as log to the base two of the number of processes.

This logarithmic growth law may occur because one processor may not communicate directly with all other processors. Instead, one processor may send information to two other processors, and each of those two processors may send information to two more processors, and so forth. Therefore, in order to model the communication that occurs in such a communication cascade, the quadratic n(n-1) coherency term in equation 4.31 should be replaced by an n*log(n) term.

Moreover, performance data that are obtained from current parallel computer systems do not always conform to Dr. Gunther's "universal" scalability "law" under other conditions. For example, a large volume of data that exceeds the capacity of the total cache memory when distributed across a few processors may well fit into total cache memory when distributed across a larger number of processors. Under these conditions, the scalability for the larger number of processors appears to grow "super-linearly" relative to the scalability of a few processors. However, Dr. Guther's model specifically disallows this "super-linear" scaling that is commonly observed. Thus, although Dr. Gunther's book is a useful introduction to the subject of measuring and modeling the behavior of parallel computer architectures, his universal scalability law should not be considered to be universal.
5 von 6 Kunden fanden die folgende Rezension hilfreich
4.0 von 5 Sternen Enlightening, however ... 11. März 2007
Von Canberra CCIE - Veröffentlicht auf Amazon.com
Format:Gebundene Ausgabe|Verifizierter Kauf
First of all, this book was worth the money I spent on it. I came away from reading this book with a clear understanding 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 in the first quarter of the book. I read on and read on looking for further conceptual gems but they weren't to be found.

I guess that books are "meant" to be at least a particular length, but this one could have been much shorter and more concise.
1 von 1 Kunden fanden die folgende Rezension hilfreich
5.0 von 5 Sternen Great coverage of Capacity Planning and Performance Management 24. August 2008
Von WIETZE A. DEVRIES - Veröffentlicht auf Amazon.com
Format:Gebundene Ausgabe|Verifizierter Kauf
Very readable coverage of Capacity Planning and Performance Management. Doesn't presume any previous knowledge, but doesn't talk down either. Several good chapters talking about queueing theory.
A great practical handbook.
2 von 3 Kunden fanden die folgende Rezension hilfreich
5.0 von 5 Sternen Who does this better? 14. März 2007
Von Ted C - Veröffentlicht auf Amazon.com
Format:Gebundene Ausgabe
I've read the other reviews and they seem to ignore the "Guerrilla" concept. The fact that scientific analysis is ignored and decisions made on perceived knowledge in most companies for me is the key to the book. Excel is a great way to get the performance point across even with precision errors. Getting management buy in is 99% of the process. GCP makes that argument simple. Read this book and get the word out. Performance is not linear!
5.0 von 5 Sternen Outstanding - Clearly focuses on the key elements to measure capacity & performance 23. Juni 2014
Von John Hinkle - Veröffentlicht auf Amazon.com
Format:Taschenbuch|Verifizierter Kauf
Neil has done a great job of defining the keys to measuring capacity requirements and techniques for getting this done when time resources are constrained.
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