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Failure inducer framework
The main features of linkedin/simoorg are: Chaos Engineering, Chaos Engineering Tools.
Projects with overlapping indexed features include: mefellows/muxy — Proxy for simulating real-world distributed system failures to improve resilience in your applications. osrg/namazu — :fish: 鯰: Programmable fuzzy scheduler for testing distributed systems. chaos-mesh/chaos-mesh — Chaos Mesh is a cloud-native fault injection tool and Kubernetes chaos engineering platform designed to verify system… shopify/toxiproxy — Toxiproxy is a framework designed for chaos engineering and network resilience testing. It functions as a programmable… marmelab/gremlins.js — gremlins.js is a JavaScript stress testing framework and web UI monkey testing library. It functions as a browser… aphyr/distsys-class — This project provides educational materials and courseware focused on the theoretical and practical foundations of…
Proxy for simulating real-world distributed system failures to improve resilience in your applications.
Chaos Mesh is a cloud-native fault injection tool and Kubernetes chaos engineering platform designed to verify system resilience. It functions as a testing framework for designing and executing automated failure scenarios to evaluate how containerized workloads recover from disruptions. The project acts as a multi-cluster chaos orchestrator, providing a centralized control plane to manage and monitor experiments across multiple remote Kubernetes clusters from a single interface. It includes a dashboard for the visual scheduling of experiments and the coordination of complex failure scenarios.
Toxiproxy is a framework designed for chaos engineering and network resilience testing. It functions as a programmable TCP proxy that intercepts and routes data streams between clients and servers, allowing developers to simulate unstable network conditions such as latency, bandwidth throttling, and connection failures. The tool provides a control plane that enables the dynamic manipulation of network conditions on active connections in real time. By integrating into automated test suites, it allows for the programmatic injection of faults to validate how distributed systems and microservices
