Awesome GitHub RepositoriesDistributed Load Generation

Vegeta is an HTTP load testing tool and library designed to measure the performance and stability of web services. It functions as a command-line utility, a programmable package for integration into other applications, and a distributed load generator capable of splitting request rates across multiple machines. The tool is distinguished by its constant-rate request scheduler, which dispatches requests at a fixed frequency regardless of target response times. It employs lazy target streaming to maintain low memory usage during large tests and uses a binary-encoded storage format to minimize di

Apache JMeter is a Java-based performance testing tool and multi-protocol traffic simulator used to analyze the stability and scalability of servers and networks. It functions as a distributed load testing framework that coordinates remote worker nodes from a single controller to generate high volumes of concurrent traffic. The project is distinguished by its ability to simulate traffic across diverse backend systems, including HTTP, JDBC, LDAP, JMS, FTP, and TCP. It provides a headless command-line interface for automated execution and a reporting system that transforms raw sample logs into

Artillery is a Node.js load testing tool and performance testing framework used to generate high-volume synthetic traffic. It functions as a distributed load generator capable of spawning traffic from cloud infrastructure and Kubernetes clusters to simulate massive user loads. The project distinguishes itself through its ability to execute browser-based load tests using headless browsers to measure client-side rendering and real user journeys. It also serves as a protocol testing framework that validates multiple communication standards and real-time protocols through complex, multi-step tran

Anteon is a distributed load testing platform and automated performance testing suite designed to simulate high-traffic user scenarios and measure system performance across multiple global locations. It functions as an infrastructure anomaly detector and a service dependency mapper, providing a performance monitoring dashboard to track real-time resource usage across cluster instances. The project distinguishes itself by combining distributed traffic generation with service dependency mapping to identify system bottlenecks through network-level tracing. It incorporates an automated validation

Autocannon is a Node.js HTTP load tester and benchmarking utility used to measure server throughput and latency. It functions as a high-performance request generator designed for stress testing web servers and APIs to analyze request-per-second capacity. The tool operates as a distributed HTTP load generator capable of aggregating results from multiple machines. It also functions as a HAR file replay tool, allowing users to reproduce specific network traffic patterns by replaying recorded HTTP archive files. The project covers broad capability areas including HTTP traffic simulation through

Gatling is a load testing framework and traffic generation engine used to measure response times and error rates under heavy load. It functions as an as-code testing library, allowing users to define high-volume traffic simulations and performance tests through programming languages rather than graphical interfaces. The system enables multi-language load simulation and the ability to model concurrent user traffic to identify infrastructure bottlenecks and stability limits. It supports a test-as-code workflow, where version-controlled scripts are integrated into build pipelines as performance

Beeswithmachineguns is a distributed load testing framework and cloud infrastructure orchestrator. It functions as an HTTP traffic generator that provisions fleets of virtual servers to simulate massive concurrent user traffic across multiple cloud regions to stress test web applications. The tool specifically manages the lifecycle of AWS EC2 micro instances, automating the provisioning of servers across different geographic zones and the subsequent termination of all active resources to prevent unnecessary billing costs. The system coordinates concurrent traffic scheduling and distributed r

HttpRunner ist ein Multi-Protokoll-Netzwerktest-Framework, das für die Automatisierung von Funktions- und Regressionstests von HTTP-Schnittstellen entwickelt wurde. Es fungiert als Multi-Protokoll-Netzwerktester, der HTTP/1.1, HTTP/2, WebSocket, TCP und RPC unterstützt, um diverse Kommunikationsmuster zu validieren. Das Projekt enthält spezialisierte Engines für API-Performance-Tests, datengesteuerte Tests und einen Testfall-Generator, der HAR-Dateien, curl-Befehle und Swagger-Definitionen in ausführbare Skripte konvertiert. Das Framework zeichnet sich durch die Trennung von Testlogik und Geschäftsdaten mittels einer datengesteuerten Execution-Engine sowie durch die Unterstützung von Lasttests mit hoher Parallelität durch verteilte Last-Orchestrierung aus. Es verfügt über ein mehrsprachiges Plugin-System, das es Benutzern ermöglicht, die Core-Engine mit benutzerdefinierter Validierungs- und Verarbeitungslogik in Go, Python oder Java zu erweitern. Das Projekt deckt ein breites Spektrum an Funktionen ab, einschließlich komplexer Szenariomodellierung für die Simulation von Benutzer-Workflows, Antwortvalidierung und detaillierter Netzwerkleistungsanalyse. Es bietet Tools für verteilte Lasterzeugung, geografisches Netzwerk-Probing und die Integration automatisierter Test-Suiten in CI-Pipelines. Die Core-Test-Engine kann über eine Kommandozeilenschnittstelle ausgeführt oder innerhalb des Python-Test-Ökosystems mittels eines dedizierten Runners eingebunden werden.