# Observability and Chaos Engineering on System Calls for Containerized Applications in Docker

arXiv: https://arxiv.org/abs/1907.13039 · HTML: https://mlsanity.com/paper/1907.13039/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 30 Jul 2019.

## Built on by (most cited first, 3 of 3)

- [AIOpsLab: A Holistic Framework to Evaluate AI Agents for Enabling Autonomous Clouds](https://mlsanity.com/paper/2501.06706/) (2025)
- [Building AI Agents for Autonomous Clouds: Challenges and Design Principles](https://mlsanity.com/paper/2407.12165/) (2024)
- [Belayer: Efficient Fault Tolerance for LLM Agentic RL Training](https://mlsanity.com/paper/2608.14635/) (2026)

## Abstract (arXiv)

In this paper, we present a novel fault injection system called ChaosOrca for system calls in containerized applications. ChaosOrca aims at evaluating a given application's self-protection capability with respect to system call errors. The unique feature of ChaosOrca is that it conducts experiments under production-like workload without instrumenting the application. We exhaustively analyze all kinds of system calls and utilize different levels of monitoring techniques to reason about the behaviour under perturbation. We evaluate ChaosOrca on three real-world applications: a file transfer client, a reverse proxy server and a micro-service oriented web application. Our results show that it is promising to detect weaknesses of resilience mechanisms related to system calls issues.