Part II. The Principles of Chaos

The performance of complex systems is typically optimized at the edge of chaos, just before system behavior will become unrecognizably turbulent.

Sidney Dekker, Drift Into Failure

The term “chaos” evokes a sense of randomness and disorder. However, that doesn’t mean Chaos Engineering is something that you do randomly or haphazardly. Nor does it mean that the job of a chaos engineer is to induce chaos. On the contrary: we view Chaos Engineering as a discipline. In particular, we view Chaos Engineering as an experimental discipline.

In the quote above, Dekker was making an observation about the overall behavior of distributed systems. He advocated for embracing a holistic view of how complex systems fail. Rather than looking for the “broken part,” we should try to understand how emergent behavior from component interactions could result in a system drifting into an unsafe, chaotic state.

You can think of Chaos Engineering as an empirical approach to addressing the question: “How close is our system to the edge of chaos?” Another way to think about this is: “How would our system fare if we injected chaos into it?”

In this chapter, we walk through the design of basic chaos experiments. We then delve deeper into advanced principles, which build on real-world applications of Chaos Engineering to systems at scale. Not all of the advanced principles are necessary in a chaos experiment, but we find that the more principles you can apply, the more confidence ...

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