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Learning Chaos Engineering: Discovering and Overcoming System Weaknesses Through Experimentation

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Most companies work hard to avoid costly failures, but in complex systems a better approach is to embrace and learn from them. Through chaos engineering, you can proactively hunt for evidence of system weaknesses before they trigger a crisis. This practical book shows software developers and system administrators how to plan and run successful chaos engineering experiments.

System weaknesses go beyond your infrastructure, platforms, and applications to include policies, practices, playbooks, and people. Author Russ Miles explains why, when, and how to test systems, processes, and team responses using simulated failures on Game Days. You’ll also learn how to work toward continuous chaos through automation with features you can share across your team and organization.

Learn to think like a chaos engineer Build a hypothesis backlog to determine what could go wrong in your system Develop your hypotheses into chaos engineering experiment Game Days Write, run, and learn from automated chaos experiments using the open source Chaos Toolkit Turn chaos experiments into tests to confirm that you’ve overcome the weaknesses you discovered Observe and control your automated chaos experiments while they are running

178 pages, Kindle Edition

Published July 12, 2019

13 people are currently reading
88 people want to read

About the author

Russ Miles

20 books2 followers

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Displaying 1 - 2 of 2 reviews
4 reviews1 follower
December 27, 2020
It's basically a presentation of what chaos engineering is, and then a presentation of the chaos toolkit.
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44 reviews1 follower
May 15, 2020
Great book to get started with Chaos Engineering. Russ makes it very live and simple and introduces us with help of open source tools. Interesting fact is that this is based on hypothesis based approaches. During this time I was discussing with Amazon for a role in a team for Customer Reliability. The significance of the subject is increasing as Software moves closer to reliability as a major consideration.
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