hey

Go supports this with `go run`, e.g. # Example 1: Running the latest version go run github.com/rakyll/hey@latest # Example 2: Running a specific version go run github.com/rakyll/hey@v0.1.4

Using cluster and worker threads. The code is here, but completely undocumented, as I’ve been side tracked by a few other things[0]. I’m currently looking into porting that project to Bun, so it’s possibly dead in its current form. I was planning on turning that into a library, but Bun nerd sniped me. You need the “hey” tool to run the benchmarks[1] the way that I was running them. [0] https://github.com/chrisdavies/sql3 [1] https://github.com/rakyll/hey

I've used LoadForge before for stress testing: https://loadforge.com I found it a good middle-ground between DIY tools like "hey" and the likes of JMeter and K6. LoadForge is really just a frontend for Locust [2] behind the scenes so all tests are written in Python which might not fit your requirement for Go/Rust, but it's affordable and quick to get started with. [1] https://github.com/rakyll/hey [2] https://locust.io

I use hey[1]. Shameless plug: I have developed a small tool called vex [2] ( using PHP ) for this purpose but it's not feature complete. [1] https://github.com/rakyll/hey [2] https://github.com/vamsiikrishna/vex

The project is very interesting but the benchmark results must be completely wrong. On my machine, using https://github.com/rakyll/hey to test: 1 concurrent request: node.js does ~8000 req/second, go does ~9000, japronto does ~10000 10 concurrent requests: node.js does ~24000 req/second, go does ~45000, japronto does ~55000 Nowhere near a million. That's without pipelining though. Can pipelining really add SO MUCH performance? UPDATE: tried wrk with pipelining. japronto does 700000, golang 150000, node 35000. Holy shit, pipelining is epic. But the benchmark is not fair when only one server supports pipelining.