# Chaos Engineering

arXiv: https://arxiv.org/abs/1702.05843 · HTML: https://mlsanity.com/paper/1702.05843/

## Key facts

- Cited by 19 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 20 Feb 2017.

## Built on by (most cited first, 19 of 19)

- [ReliabilityBench: Evaluating LLM Agent Reliability Under Production-Like Stress Conditions](https://mlsanity.com/paper/2601.06112/) (2026)
- [A Trace-Based Assurance Framework for Agentic AI Orchestration: Contracts, Testing, and Governance](https://mlsanity.com/paper/2603.18096/) (2026)
- [Assessing and Enhancing the Robustness of LLM-based Multi-Agent Systems Through Chaos Engineering](https://mlsanity.com/paper/2505.03096/) (2025)
- [Assessing High-Risk AI Systems under the EU AI Act: From Legal Requirements to Technical Verification](https://mlsanity.com/paper/2512.13907/) (2025)
- [Decoupled DiLoCo for Resilient Distributed Pre-training](https://mlsanity.com/paper/2604.21428/) (2026)
- [When Errors Become Narratives: A Longitudinal Taxonomy of Silent Failures in a Production LLM Agent Runtime](https://mlsanity.com/paper/2606.14589/) (2026)
- [Tangent: An Empirical Study of Testing Practices for LLM-Based Agent Applications](https://mlsanity.com/paper/2608.08413/) (2026)
- [Agile, Antifragile, Artificial-Intelligence-Enabled, Command and Control](https://mlsanity.com/paper/2109.06874/) (2021)
- [ADA: Automated Moving Target Defense for AI Workloads via Ephemeral Infrastructure-Native Rotation in Kubernetes](https://mlsanity.com/paper/2505.23805/) (2025)
- [AutoGuard: A Self-Healing Proactive Security Layer for DevSecOps Pipelines Using Reinforcement Learning](https://mlsanity.com/paper/2512.04368/) (2025)
- [Binding Drift in Multi-Step Tool-Augmented Agents](https://mlsanity.com/paper/2607.18316/) (2026)
- [When Agentic Executions Fail: Detecting and Localizing Runtime Faults from Telemetry](https://mlsanity.com/paper/2608.14680/) (2026)
- [LLM-Powered Fully Automated Chaos Engineering: Towards Enabling Anyone to Build Resilient Software Systems at Low Cost](https://mlsanity.com/paper/2511.07865/) (2025)
- [ICAN-Deploy: Identity-Stable Canary Deployment for Safety-Critical Embodied Agents](https://mlsanity.com/paper/2605.28097/) (2026)
- [Unsafe at any AUC: Unlearned Lessons from Sociotechnical Disasters for Responsible AI](https://mlsanity.com/paper/2607.14353/) (2026)
- [Towards Risk-free AI Agent Deployment](https://mlsanity.com/paper/2608.16411/) (2026)
- [Reality Is the Final Verifier: On Two Key Gaps in Agentic Software Engineering](https://mlsanity.com/paper/2609.12039/) (2026)
- [Measurement Boundaries in LLM Financial Agent Evaluation: Fixed-Tape Execution and Multi-Defect Auditing](https://mlsanity.com/paper/2609.32379/) (2026)
- [When Messages Go Wrong: Understanding Communication Faults in LLM-Based Multi-Agent Systems](https://mlsanity.com/paper/2610.15459/) (2026)

## Abstract (arXiv)

Modern software-based services are implemented as distributed systems with complex behavior and failure modes. Many large tech organizations are using experimentation to verify the reliability of such systems. We use the term "Chaos Engineering" to refer to this approach, and discuss the underlying principles and how to use it to run experiments.