Systems fail in unexpected ways under real-world conditions. Chaos engineering proactively discovers weaknesses by intentionally introducing failures. Rather than waiting for outages to reveal problems, teams inject controlled chaos to build confidence in system resilience.
Chaos Experiments
Start with hypotheses about system behavior under failure. What happens when a database becomes unavailable? How do services respond to network latency? Experiments test these hypotheses in controlled conditions, revealing gaps between expected and actual behavior.
- Begin chaos experiments in staging environments before production
- Start small—kill single instances before simulating datacenter failures
- Define steady state metrics to measure experiment impact
- Automate experiments for regular execution catching regressions
- Document findings and improvements from each experiment
Tooling Options
Chaos Monkey randomly terminates instances. Gremlin provides comprehensive chaos-as-a-service. LitmusChaos offers Kubernetes-native chaos engineering. AWS Fault Injection Simulator integrates with AWS services. Choose tools matching your infrastructure and team expertise.