Jmeter
Showing 36 of 61 projects
An open-source continuous testing platform with AI assistant, integrating test management, API testing, and team collaboration.
An extensible open source load testing tool for advanced Linux users, supporting multiple load generators and performance analytics.
A lightweight HTTP load testing tool written in Rust with an Ansible-inspired YAML syntax for defining benchmarks.
Automation-friendly framework for continuous testing that wraps JMeter, Gatling, Locust.io, and Selenium WebDriver.
A curated collection of resources covering Apache JMeter usage, including plugins, integrations, testing techniques, and DevOps practices.
A curated collection of resources covering Apache JMeter usage, including plugins, integrations, testing techniques, and DevOps practices.
A JMeter plugin for visually stress testing Apache Dubbo interfaces with support for multiple Dubbo and JMeter versions.
A shell script that automates distributed load testing by running Apache JMeter tests on Amazon EC2 instances or custom host lists.
A Maven plugin that integrates Apache JMeter performance tests into your Maven build lifecycle.
A Docker-based framework for comprehensive performance testing, combining backend load testing with Apache JMeter and frontend testing with sitespeed.io and WebPageTest.
A load testing as a service (LTaaS) platform that runs Apache JMeter clusters on Kubernetes and OpenShift for scalable performance testing.
A web dashboard for analyzing, running, and monitoring JMeter load tests with continuous integration support.
Converts Postman collections (V2+) to JMeter JMX files for performance testing.
A JMeter plugin that exposes performance test results as Prometheus metrics via an HTTP API.
A JMeter plugin for load testing gRPC services without requiring pre-compiled protobuf classes.
A Kubernetes-native platform for running isolated performance tests using various load generators like JMeter, Locust, and k6.
Generate beautiful, customizable performance reports from JMeter, Locust, and other testing tools.
A Python API for scripting JMeter performance tests using Java JMeter-DSL via pyjnius.
Azure DevOps pipeline for scalable cloud load testing using Apache JMeter and Terraform to dynamically provision Azure Container Instances.
A Python tool that converts Swagger/OpenAPI and YApi documentation into JMeter JMX files for automated performance testing.
JMeter plugin that sends test results to ElasticSearch for live monitoring and visualization.
A starter kit for running distributed JMeter load tests in Kubernetes with live monitoring, reporting, and a mocking service.
A JMeter plugin that writes load test metrics directly to InfluxDB in real-time.
Converts JMeter .jmx files to k6 JavaScript code for performance testing.
A distributed load testing tool that scales JMeter tests across multiple hosts using a master-slave architecture.
A Maven plugin that parses JMeter result files and generates detailed performance analysis reports with charts.
Converts Fiddler or Charles session files into JMeter 4.0+ JMX scripts for automated HTTP interface testing and load testing.
A JMeter plugin for load testing HTTP Live Streaming (HLS) and MPEG-DASH video streaming protocols.
A Gradle plugin for running Apache JMeter performance and load tests within Gradle builds.
Docker-based solution for running distributed JMeter load tests on AWS ECS with automated orchestration.
A JMeter plugin for load testing gRPC services with support for protocol buffers and performance reporting.
An API that provides full JMeter functionality as code, allowing GUI-designed objects to be written programmatically.
A bootstrap project that downloads JMeter and plugins, provides examples, and simplifies load test setup for CI environments.
A JMeter HTML report generator using JAMON that replaces XSLT-based reporting with scalable StAX parsing and SLA-focused visualizations.
A scalable load testing framework using Apache JMeter on Azure Kubernetes Service with real-time Grafana dashboards.
JEval evaluates JMeter test plans and provides recommendations before performance testing begins.
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