Feedback Control for Computer Systems Paperback – 3 Nov 2013
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Introducing Control Theory to Enterprise Programmers
About the Author
Philipp K. Janert was born and raised in Germany. He obtained aPh.D. in Theoretical Physics from the University of Washington in 1997and has been working in the tech industry since, including four yearsat Amazon.com, where he initiated and led several projects to improveAmazon's order fulfillment process. He is the author of two books ondata analysis, including the best-selling "Data Analysis with OpenSource Tools" (O'Reilly, 2010), and his writings have appeared onPerl.com, IBM developerWorks, IEEE Software, and in the LinuxMagazine. He has contributed to CPAN and other open-sourceprojects. He lives in the Pacific Northwest.
Most helpful customer reviews on Amazon.com
According to the book, Feedback Control is a topic well known to mechanical engineers, but not so much in the software industry. Feedback Control is about making smarter systems that can cope with dynamic environments. Many knobs that developers build into configuration can actually be automated with feedback loops.
Examples given early in the book:
* A Cache by tracking hit rate and changing the cache size
* A Server Farm by tracking request latency and changing number of deployed server nodes
* A Queueing System by tracking wait time and changing the number of workers
* A Graphics Library by tracking memory consumption and changing the output resolution
The book is well written. It starts out with practical examples and working code. It later introduces the deep theory and drops some math bombs. Don't worry, there is Python code for everything and you don't have to understand the math.
It gives solid advice, like don't blindly use Feedback Control for optimization; optimization needs a higher level strategy guiding the process.
Lastly, there are references for further reading, if you do want to work through more of the theory.
The term Enterprise is thrown about, don't let this scare you away :) This is a valuable book for many types of software problems. A couple I've brainstormed while reading:
* Controlling difficulty of a video game, to react to how skilled a player is
* Controlling aspects of an animation
* Controlling polling of APIs for fresh data
* Driving load testing to find different scaling points (errors, high latency, etc)
Well done and thanks for filling a much needed segment of software fundamentals.
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