Chaos Engineer

Designs controlled failure experiments — from a single fault injection to a full game day — and produces the runbook, rollback plan.

Development / DevOps & Infradevelopmentdevops-infra
by AgentVoltv1.0.0Published 1y ago1 install
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Before & after

Same prompt, same agent — the only difference is the skill.

PromptDesign a chaos experiment for our infrastructure.
Beforegeneric AI agent
Designing chaos experiments is a good way to test how resilient your system is to failures. The basic idea is to introduce failures in a controlled way and see how your system responds. You might experiment with things like taking down a service, increasing latency, or simulating a database failure. You'd want to define what you're trying to learn, set up the experiment carefully so you can control the failure, observe what happens, and then have a rollback plan in case things go wrong. You should probably start with smaller, lower-risk experiments and work your way up to more severe scenarios. If you can tell me about your system architecture and what failure scenarios you're most concerned about, I can help you design a specific experiment.
Afterwith Chaos Engineer
CHAOS EXPERIMENT DESIGN: API LATENCY INJECTION

EXPERIMENT OBJECTIVE
Test: How does the system handle when payment-processing API responds in 5 seconds instead of 200ms?
Success criteria: Orders queue instead of failing; no 500 errors; recovery within 30 seconds of latency removal

EXPERIMENT MANIFEST
Title: Payment API Degradation
Timing: Tuesday 2pm UTC (low-traffic window, not Friday evening)
Duration: 10 minutes (bounded blast radius)
Target service: Payment processor (East region first)

FAILURE INJECTION MECHANISM
Tool: Chaos Monkey (Netflix; inject latency via proxy)
Configuration:
  Service: paymentgateway-api
  Failure type: Network latency
  Latency added: 4.8 seconds (5s total response time)
  Percentage: 100% (all payment calls)
  Region: us-east-1 (primary only, not backup)

METRICS TO MONITOR (Real-time dashboard)
• Payment success rate (target: stays > 90%)
• API response time p99 (expect: 5+ seconds during experiment)
• Order queue depth (should increase, then drain after recovery)
• Error rate (target: stays < 1%)
• Customer-facing latency (web checkout time)

BLAST RADIUS ASSESSMENT
• Blast radius: Payment flow only; checkout page slows but doesn't error
• Customers impacted: Checkout users during 10-min window (est. 1-2K transactions)
• Critical risk: If queue overflows -> orders lost (MITIGATED by queue monitoring)

ROLLBACK PROCEDURE
Manual kill-switch: Kill chaos experiment pod (1 minute to recover)
Automatic rollback: If order queue > 5K, abort experiment (prevents cascade)
Verification: Confirm payment success rate > 95% within 2 min of rollback

POST-MORTEM TEMPLATE
• What we learned: System handles graceful degradation; queue strategy works
• Gaps identified: Alerts triggered late (should alert at queue 1K)
• Follow-up: Add health-check endpoint for payment queue depth
• Next experiment: Test database failover (higher risk, requires pre-approval)

About this skill


name: chaos-engineer description: Use when Designs chaos experiments, creates failure injection frameworks, and facilitates game day exercises for distributed systems — producing runbooks, experiment manifests, rollback procedures, and post...

Chaos Engineer

Designs chaos experiments, creates failure injection frameworks, and facilitates game day exercises for distributed systems — producing runbooks, experiment manifests, rollback procedures, and post-mortem templates. Use when designing chaos experiments, implementing failure injection frameworks, or conducting game day exercises. Invoke for chaos experiments, resilience testing, blast radius control, game days, antifragile systems, fault injection, Chaos Monkey, Litmus Chaos.

What you get

  • Public GitHub repo
  • the skills/chaos-engineer folder with SKILL.md and references.

Customize your output

  • Fork the repo and extend the skill's reference files for your own stack conventions.

Example output

Activates on a matching request (e.g. building or reviewing Chaos Engineer code) and can chain with other skills in the pack.

Best for

Full-stack developers and engineering teams using Claude Code.

SKILL.md preview

SKILL.md
---
name: chaos-engineer
description: Designs chaos experiments, creates failure injection frameworks, and facilitates game day exercises for distributed systems.
version: 1.0.0
category: Development / DevOps & Infra
author: AgentVolt
license: proprietary
tags:
  - development
  - devops-infra
---

# Chaos Engineer

Designs controlled failure experiments — from a single fault injection to a full game day — and produces the runbook, rollback plan, and post-mortem template that make it safe to run.

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