Chaos Engineering Checklist
Design a chaos experiment step by step. Fill in the hypothesis, select failure types, check off each phase, and generate a runbook to share with your team.
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Experiment Builder
Pre-Experiment
Complete all steps before starting the experiment
Experiment Types
Select which failure modes will be tested
During Execution
Steps to follow while the experiment is running
Post-Experiment
Complete after the experiment ends
Experiment Runbook
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See what's included → Browse all deals →Frequently Asked Questions
What is chaos engineering?▼
Chaos engineering is the discipline of experimenting on a system in order to build confidence in its ability to withstand turbulent and unexpected conditions in production. Pioneered at Netflix, it involves deliberately injecting failures (latency, service outages, resource exhaustion) to discover weaknesses before they cause real outages. The goal is to move from reactive incident response to proactive resilience building.
What is a steady state hypothesis?▼
A steady state hypothesis defines what 'normal' looks like for your system — a measurable output that shows the system is behaving correctly. Examples: '99th percentile API latency is under 200ms', 'checkout success rate is above 99.5%', 'error rate is below 0.1%'. Chaos experiments validate that this steady state is maintained even when failures are injected. If steady state breaks, you have found a real weakness.
What is blast radius?▼
Blast radius is the scope of impact if an experiment goes wrong. A full blast radius means the entire system is affected. Partial means a subset of traffic or nodes. Single-instance means only one pod or server. Best practice is to start with the smallest possible blast radius (single instance, canary traffic) and expand as you gain confidence. Always have a rollback plan that can return to steady state quickly.
When should I run chaos experiments in production?▼
Only run in production when you have: validated the experiment in staging, defined and measured your steady state baseline, set clear abort conditions, ensured monitoring and alerting are in place, notified on-call teams, and have a tested rollback plan ready. Start with a very small blast radius (single instance or 1% of traffic). Many organisations run chaos experiments during business hours when the full team is available to respond.
What tools are used for chaos engineering?▼
Popular chaos engineering tools include: LitmusChaos (Kubernetes-native, CNCF project), Chaos Monkey (Netflix, terminates random EC2 instances), Gremlin (SaaS platform, broad failure types), AWS Fault Injection Simulator (FIS), Chaos Mesh (Kubernetes), Pumba (Docker), and Toxiproxy (network-level latency/failure injection for integration tests). For game days and manual experiments, this checklist provides a structured approach without requiring any tooling.