chaos-engineering

Inject network failures, resource exhaustion, and service disruptions to test system resilience.

Updated Aug 23, 2026

Search Tags:#resilience #disaster recovery #stress testing #system reliability #chaos engineering #fault tolerance

Ready to run

npx skills add https://github.com/toddbadams/SBFoundation --skill chaos-engineering-toddbadams

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: chaos-engineering
Source: https://github.com/toddbadams/SBFoundation/tree/main/.claude/skills/operations/chaos-engineering
Command: npx skills add https://github.com/toddbadams/SBFoundation --skill chaos-engineering-toddbadams

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires stress, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill helps identify and address weaknesses in system reliability by simulating various failure conditions in a controlled manner.

Core Features & Use Cases

Controlled Failure Injection: Intentionally introduce network latency, packet loss, resource exhaustion, or service outages.
Hypothesis Testing: Validate system behavior under stress and confirm fault tolerance mechanisms.
Use Case: Before a major deployment, use this Skill to simulate a 10% packet loss on a critical microservice to ensure it degrades gracefully and doesn't cause a full outage.

Quick Start

Run a chaos experiment to test network latency on the eth0 interface.

Frequently Asked Questions about chaos-engineering

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I test system resilience and fault tolerance before a major deployment?▼

To test system resilience, you run controlled chaos engineering experiments that intentionally inject network failures, resource exhaustion, or service disruptions. This validates system behavior and confirms degradation mechanisms under adverse conditions.

What is chaos engineering and how does it improve system reliability?▼

Chaos engineering is the discipline of simulating failure conditions like packet loss or service outages in a controlled manner. It improves system reliability by identifying weaknesses and validating fault tolerance mechanisms before actual disasters occur.

How do I simulate network latency and packet loss on a specific interface?▼

You can simulate network latency and packet loss on interfaces like eth0 using command-line tools to inject controlled failures. This allows you to test whether critical microservices degrade gracefully without causing a full outage.

Does this chaos engineering approach require the stress tool to inject resource exhaustion?▼

Yes, injecting resource exhaustion and other system disruptions relies on the stress command-line dependency. It provides the necessary functionality to simulate adverse conditions and validate fault tolerance during testing.

Can I use this to validate hypothesis testing for microservice fault tolerance?▼

Yes, you can validate hypothesis testing for microservice fault tolerance by intentionally introducing service disruptions. This confirms whether your system behaves as expected under stress and degrades gracefully during failures.

What are the limitations of using command-line tools for disaster recovery testing?▼

Using command-line tools for disaster recovery testing limitations include the need for careful execution to avoid uncontrolled outages. Experiments must be scoped precisely to inject failures safely without causing unintended full system disruptions.