Implementing Chaos Engr. in a Risk Averse Culture
summary
Practical playbook for getting chaos engineering past risk-averse leadership: define a measurable steady state and build experiments only after observability is in place, run automated low-blast-radius experiments and pilot programs, and speak ROI via total cost of ownership. Concrete case: replicated environment for Splunk customer to rehearse failures, requested $5M investment to migrate ~15,000 instances to Graviton over eight months, yielding large cost and performance gains. Tools referenced: Chaos Monkey, Gremlin, Litmus, Chaos Mesh.
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chapters (12)
- 0:00intro
- 0:22preamble
- 0:35about me
- 2:17evolution of system architecture
- 5:59what is chaos engineering?
- 7:55principles of chaos engineering
- 10:35conservative mindset
- 14:28selling chaos engineering
- 19:19gaining buy in
- 22:11splunkcloud case study
- 26:35tools & resources
- 26:56thank you
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