Chaos Engineering

Chapter 1. Why Do Chaos Engineering?

Chaos Engineering is an approach for learning about how your system behaves by applying a discipline of empirical exploration. Just as scientists conduct experiments to study physical and social phenomena, Chaos Engineering uses experiments to learn about a particular system.

Applying Chaos Engineering improves the resilience of a system. By designing and executing Chaos Engineering experiments, you will learn about weaknesses in your system that could potentially lead to outages that cause customer harm. You can then address those weaknesses proactively, going beyond the reactive processes that currently dominate most incident response models.

How Does Chaos Engineering Differ from Testing?

Chaos Engineering, fault injection, and failure testing have a large overlap in concerns and often in tooling as well; for example, many Chaos Engineering experiments at Netflix rely on fault injection to introduce the effect being studied. The primary difference between Chaos Engineering and these other approaches is that Chaos Engineering is a practice for generating new information, while fault injection is a specific approach to testing one condition.

When you want to explore the many ways a complex system can misbehave, injecting communication failures like latency and errors is one good approach. But we also want to explore things like a large increase in traffic, race conditions, byzantine failures (poorly behaved nodes generating faulty responses, ...