Catch the Failures That Take You Down — Before Production Does
We deliberately break your systems in a controlled way to surface a dozen hidden failure modes before they surface during a 2 a.m. outage.
Untested assumptions fail under load
Failover, retries, and backups all 'should work', until the day they quietly don't.
MTTR is a guess, not a number
Without practice, your time-to-recovery is whatever it happens to be on the worst possible day.
Hidden dependencies cascade
One overlooked dependency can turn a small failure into a full outage no one saw coming.
Incidents become learning by disaster
Teams discover their weak points during real customer-facing outages instead of controlled experiments.
Untested resilience
- Failover documented but never exercised
- MTTR unknown until a real incident
- Single points of failure discovered too late
- On-call learns the system during outages
- Post-mortems repeat the same surprises
Korur chaos engineering
- Failure modes triggered and proven in controlled tests
- MTTR measured, tracked, and improved
- Single points of failure found and fixed proactively
- On-call rehearses real scenarios safely
- Each experiment hardens the system measurably
Define steady state
We establish what 'healthy' looks like in measurable terms before touching anything.
SetupForm a hypothesis
We predict how the system should behave when a specific component fails.
Inject controlled failure
We trigger the failure in a blast-radius-limited way, with a kill switch ready.
Per experimentMeasure & compare
We compare actual behavior against the hypothesis and capture the gaps.
Harden & repeat
Findings drive fixes; experiments are automated so resilience keeps improving.
OngoingInstance & node termination
Kill compute on demand to prove auto-healing and failover actually work.
Network latency & partition
Inject delays and splits to surface fragile timeouts and retry storms.
Dependency outages
Take down databases, queues, and third-party APIs to test graceful degradation.
Resource exhaustion
Starve CPU, memory, and disk to validate limits and back-pressure.
Region & zone failure
Simulate losing an availability zone to verify multi-region recovery.
Traffic surges
Drive load spikes to confirm scaling and rate-limiting hold under pressure.
Compute and container orchestration
Databases and data stores
Message queues and event streams
Third-party API dependencies
Load balancers and networking
Auto-scaling and failover logic
Backup and restore procedures
Observability and alerting paths
On-call and incident runbooks
- 1
Assess & baseline
Week 1-2Map the architecture, define steady state, and identify candidate experiments.
- 2
First controlled experiments
Week 3-4Run low-blast-radius experiments in staging, then carefully in production.
- 3
Harden & automate
Month 2Fix what breaks and automate recurring experiments into your pipeline.
- 4
Continuous practice
OngoingChaos becomes a routine, scheduled discipline owned by your team.
Faster recovery
Lower MTTR because your team has rehearsed real failures.
Fewer surprises
Single points of failure are found in tests, not outages.
Confident on-call
Engineers trust the system because they've watched it recover.
Resilient by design
Hardening becomes a continuous habit, not a one-off project.
We thought our failover worked. The first experiment proved it didn't, in staging, where it was cheap to fix.
Our MTTR dropped by nearly half once the on-call team had actually practiced the scenarios.
Chaos days turned anxiety into confidence. We now ship faster because we trust our recovery paths.
The Challenge
Northwave's SaaS platform had grown fast and passed every functional test, but nobody knew how it behaved under real failure. Load testing showed healthy averages, yet the team had a nagging suspicion that the green dashboards were hiding fragile dependencies.
Our Solution
Korur designed a series of controlled chaos experiments against a production-like environment: killing instances, injecting network latency, throttling the database connection pool and severing third-party dependencies one at a time. Each experiment had a clear hypothesis and a defined blast radius so nothing ran uncontrolled.
Know Your Failures Before Production Does
Every system breaks somewhere. We'll find your breaking points safely, in controlled chaos. Your team learns. Your confidence skyrockets. Your customers never see downtime.