KRKN: Chaos and Resiliency Testing for Kubernetes

Introduction

Most production outages don’t start as “everything is down.” They start as a slow API, a flaky network segment, a node that goes NotReady at the worst time—and then a cascade of retries, timeouts, and noisy alerts that make recovery harder.

KRKN, accepted as a CNCF Sandbox project in 2024, is a chaos and resiliency testing tool for Kubernetes that injects failures into clusters to assess how systems behave under turbulent conditions. With CI-friendly workflows across private and public clouds, it’s designed to help teams turn resilience from an assumption into something they can continuously validate.

Chaos Testing

• Failure injection enables injection of various failure scenarios.
• Network failures enable testing network failure scenarios.
• Node failures enable testing node failure scenarios.
• Pod failures enable testing pod failure scenarios.

Resiliency Assessment

1. Recovery testing enables testing of recovery mechanisms.
2. Failover testing enables testing of failover capabilities.
3. Health checking enables monitoring of cluster health during chaos.
4. Metrics collection provides metrics for resiliency analysis.

CI Integration

• Pipeline integration enables integration with CI/CD pipelines.
• Automated testing enables automated chaos testing in pipelines.
• Reporting provides detailed reports on resiliency testing.
• Alerting enables alerting on resiliency issues.

Multi-Cloud Support

• Private cloud support enables testing in private cloud environments.
• Public cloud support enables testing in public cloud environments.
• Hybrid cloud support enables testing across hybrid cloud environments.
• Multi-cluster support enables testing across multiple clusters.

Use Cases

• Resiliency validation enables validation of cluster resiliency.
• Disaster recovery testing enables testing of disaster recovery procedures.
• Capacity planning enables planning for failure scenarios.
• Compliance testing enables testing of compliance requirements.

Practical notes (how to get value without chaos-for-chaos’ sake)

• Start with a hypothesis: pick one failure mode and define “success” (SLO impact, recovery time, alert quality) before you run a scenario.
• Run in stages: begin in a non-production environment, then graduate to production with tight blast-radius controls.
• Watch the control plane too: resilience isn’t only app pods—API server pressure, DNS behavior, and node churn are common multipliers.

Summary

KRKN represents a significant advancement in chaos engineering, providing teams with powerful capabilities for testing cluster resiliency.