Principles of Chaos Engineering

Our summary

Defines chaos engineering as experimenting on a system to build confidence in its ability to withstand turbulent production conditions — controlled fault injection measured against a steady-state baseline.

Why it matters

The manifesto behind chaos engineering for AI systems: inject the failures production will throw (timeouts, malformed responses, truncated context) and test whether the system recovers.

Cited by these methods

Cite this