COMPEL Glossary / chaos-engineering
Chaos Engineering
Chaos engineering is the discipline of deliberately introducing controlled failures, disruptions, and adverse conditions into a system's production or staging environment to test its resilience and discover weaknesses before they cause real incidents.
What this means in practice
For AI systems, chaos engineering might involve injecting corrupted data into a pipeline, simulating cloud provider outages, introducing latency spikes into model serving infrastructure, or disabling monitoring components. Organizations that practice chaos engineering build confidence that their AI systems will degrade gracefully rather than catastrophically when real problems occur. In COMPEL, chaos engineering is referenced in Module 3.3, Article 6 on scalability and performance architecture as an advanced practice for organizations at higher maturity levels in the Technology pillar.
Why it matters
Organizations that test only under ideal conditions discover AI system weaknesses only when real production failures occur — often at significant cost. Chaos engineering builds confidence that AI systems degrade gracefully under adverse conditions by deliberately introducing controlled failures before they happen organically. This proactive approach to resilience testing is far less expensive than learning about weaknesses through actual incidents.
How COMPEL uses it
Chaos engineering is an advanced practice within the Technology pillar, typically appropriate for organizations at higher maturity levels. During Model, chaos engineering practices are designed as part of the scalability and performance architecture. The Produce stage implements controlled failure injection in staging or production environments. The Evaluate stage reviews chaos engineering results to identify resilience gaps, and findings feed into the Learn stage's infrastructure improvement priorities.
Related Terms
Other glossary terms mentioned in this entry's definition and context.