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Chaos engineering systems invented at KTH Royal Institute of Technology.

License: MIT License

Java 0.78% Python 63.74% C++ 33.75% Makefile 0.12% QMake 0.01% Shell 0.18% C 0.47% HTML 0.02% JavaScript 0.01% CSS 0.03% Gnuplot 0.01% MATLAB 0.05% Click 0.03% Perl 0.39% Batchfile 0.01% Dockerfile 0.02% Smarty 0.01% Jupyter Notebook 0.37% SWIG 0.01%

royal-chaos's Introduction

Royal Chaos Travis Build Status

This repository contains the chaos engineering systems invented at KTH Royal Institute of Technology. Every tool is organized in a separate folder in this repo, with a detailed README file inside.

ChaosMachine

ChaosMachine is a tool to do chaos engineering at the application level in the JVM. It concentrates on analyzing the error-handling capability of each try-catch block involved in the application by injecting exceptions.

TripleAgent

TripleAgent is a system for fault injection for Java applications. The unique feature of this system is to combine automated monitoring and automated perturbation injection. It outputs concrete hints to improve the resilience against unhandled exceptions.

Chaos-NS-3

We seek to attain a simplified illustration about chaos engineering applied on a simulated Netflix environment in ns-3 with the intention to provide some enlightenment for the principles of chaos engineering and in addition to this we will also present a suggestion about how to infer an unknown system as a possible application, derived from the knowledges acquired from our chaos journey.

ChaosOrca

ChaosOrca is a tool for doing Chaos Engineering on containers by perturbing system calls for processes inside containers. Where monitoring/observability is a key part of the system to be able to reason about the given perturbations effect on the container. The system utilises strace built in system call fault injections, as such it can add delays, return error codes, do so intermittenly and more. Metrics recorded are System calls, HTTP, Logs and Performance related ones.

POBS

POBS is an approach that automatically augments Docker images to have improved observability and fault injection capabilities for Java applications.

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