Chaos Engineering & Resilience Testing

Chaos engineering injects controlled failures—network, instance, disk, CPU—into development, staging, or production to validate fault tolerance and recovery procedures safely. Experiments include automatic rollback to limit blast radius and observation of system behavior under stress.

Define steady-state metrics before injecting failures: response latency, error rates, throughput, and service availability. Compare these metrics during and after the controlled failure to confirm the system detects deviations and recovers within acceptable bounds.

Chaos experiments generate documented recovery procedures—runbooks—that capture what failed, how the system responded, and the manual or automated steps required to restore normal operation. These procedures strengthen disaster-recovery validation and team readiness.

Yes. Chaos engineering is designed for production validation with automatic rollback and blast-radius control to limit impact. Start with low-blast experiments on non-critical services, monitor deviations in real time, and expand scope as confidence grows.

Inject realistic failures: network latency and packet loss, instance or container termination, disk space exhaustion, CPU saturation, and downstream service timeouts. Each targets different failure modes—connectivity, availability, resource contention—to expose gaps in fault handling.

Yes. Establish metrics, logs, and traces before running experiments so you can observe system behavior and detect deviations from steady state. Observability tools surface whether the system recovers automatically or requires manual intervention.