This article explains how to combine dynamic and static performance testing models in FunTester by adding asynchronous console commands to control thread‑pool scaling and QPS adjustments, providing step settings, incremental changes, and graceful termination through simple key inputs.
This article explains how to filter early response times and compute detailed latency metrics—including percentiles, average, and median—within the FunTester load‑testing framework by redesigning data collection structures and adding a unified statistics method.
This article demonstrates how to use the FunTester framework to benchmark MySQL SELECT and UPDATE statements, providing sample scripts, execution results, and insights into performance tuning for typical workloads and discusses observed QPS values.
This article walks through using the FunTester framework to benchmark MySQL insert and delete operations, showing Java code examples, test configurations, and JSON results that reveal a high QPS for inserts and a noticeable slowdown when deletions are performed.
This article explains how to redesign the FunTester framework to enable real‑time pressure scaling by treating each multithreaded task as a manageable object, adding interrupt capabilities, and implementing global management for dynamic thread addition, removal, and cloning during load testing.
This article details the design and implementation of a dynamic pressure model for the FunTester performance testing framework, covering the goal of flexible load adjustments, core features, multithread synchronization using Phaser, code examples, a demo execution, console output analysis, and identified limitations.
This article demonstrates how to use the FunTester framework to benchmark Redis hash (map) and INCR commands, detailing the test design, Java code implementation, multithreaded execution, and summarizing the observed performance results.
This article presents a detailed multi‑threaded performance benchmark of Redis list commands using the FunTester framework, describing three test scenarios, Java implementation details, raw JSON results, and observations on QPS and latency for insert, pop, and combined add‑remove operations.
This article walks through a practical performance test for continuously adding key‑value pairs to Redis using the FunTester framework, detailing the test design, Java and Groovy implementations, execution logs, result metrics, and key takeaways for future Redis benchmarking.
This tutorial walks through building HTTP interface tests with the FunTester framework in Java, covering request types (GET, POST), headers, cookies, response parsing, JSON handling, and resource cleanup, and provides code examples for each step.
This tutorial walks you through installing Groovy, configuring environment variables, cloning the FunTester repository, building with Gradle, and running a simple hello‑world test case, while also detailing the framework's project structure and essential code snippets.
After a weekend of code refactoring, asynchronous processing, and removing unnecessary statistics, the author increased FunTester's QPS from 104,375 to 118,904 (≈13.9% gain), reduced memory consumption by over 57%, and documented detailed performance impacts of various optimizations with code samples and benchmark tables.
In a series of local benchmarks on a 2.6 GHz six‑core Intel i7 machine, the author compares K6, Gatling, and FunTester under 10 k to 20 k QPS loads, detailing CPU, memory, and response‑time metrics, analyzing script languages, JVM settings, and offering optimization suggestions for FunTester.
This article introduces a flexible, script‑driven performance testing approach built on the FunTester framework, explains how to write Groovy/Java test scripts, demonstrates a demo implementation with reflection‑based execution, and covers test case creation, transmission, and execution for HTTP‑based load testing.
This article benchmarks four load‑testing frameworks—JMeter, k6, Locust, and FunTester—across multiple concurrency levels, measuring CPU, memory, QPS and response time to reveal each tool’s strengths, weaknesses, and scalability limits.
The second FunTester sharing session covered HttpClient basics, FunTester’s encapsulation of HttpClient, and practical functional and performance testing techniques, providing resources, code examples, and templates for effective Java interface testing.
This article walks through the design and implementation of a Docker‑based distributed performance testing framework using FunTester, detailing the master‑scheduler, slave agents, test case packaging, code examples, and sample results for load‑testing a target service.
This article introduces the FunTester distributed testing framework, explains its single‑node HTTP API, provides complete Java, generic Java, and Groovy code examples, details request parameters, response structure, and the underlying PerformanceResultBean class for analyzing test results.
This article explains how to design and implement distributed performance testing cases using jar‑method invocations, demonstrates a Java demo with reflection‑based execution, discusses common pitfalls, and shows how to package, deploy, and run the test cases within a Docker‑enabled environment.
This article explains how to transform a Java HttpRequestBase object into an equivalent curl command, enabling rapid request replay across servers and detailed timing analysis, and demonstrates the process with step‑by‑step code examples and a functional test using the FunTester framework.
This article presents a detailed walkthrough of the FunTester testing framework architecture, covering its layered design, core modules for single‑ and multi‑project setups, multi‑protocol support, common request handling, business logic encapsulation, test flow, data construction techniques, and auxiliary tools such as moco API and JsonPath.
During the Chinese New Year break the author used draw.io (now diagrams.net) to create a comprehensive architecture diagram of the FunTester testing framework, outlining its functional and performance layers, supported protocols, utility modules, and multithreaded execution model.
This article presents a practical demo for multi‑chain performance testing with FunTester, describing the overall workflow, custom multithreaded implementation, Java code example, and sample console output to illustrate how to execute and analyze load tests across multiple request paths.
This article explains how to capture all HTTP requests from a browser, filter out irrelevant assets, convert them into HttpRequestBase objects, and run a concurrent load test across multiple APIs using the FunTester framework, complete with code snippets and performance metrics.
This article describes how to implement a multi‑interface performance test for the collect and uncollect operations of a teacher’s resource list, using Groovy scripts, a custom FunTester framework, multithreaded request generation, request‑id tracking, and response recording to produce QPS and RT metrics.
This article walks through implementing and testing a POST API using the FunTester framework, covering a complete Java demo, handling parameter dependencies, authentication flow, and practical tips for short‑term test projects, with a full code example and a Gitee repository link.
This article walks through building and executing an HTTP GET request to Tencent Weather's API using the FunTester framework in Java, showing how to assemble parameters, send the request, parse the JSON response, and verify key data points.
