This product was not featured by Product Hunt yet. It will not be visible on their landing page and won't be ranked (cannot win product of the day regardless of upvotes).
loadr
Find the breaking point — load testing in one Rust binary
One prompt. While Claude Fable 5 was briefly available, we asked it to build a load tester in Rust that combined the best of k6, JMeter, Gatling and Locust — plugins, embedded scripting, distributed execution. It returned a real foundation, not a toy. We kept building. Today it's one Rust binary with declarative YAML + JavaScript tests, exact percentiles (HDR histograms — p99.9 is real, not sampled), installable protocol/datastore plugins, a live web UI, distributed agent runs and a CI gate.
Hey everyone, maker here 👋
The origin story's up in the description, but the short version is loadr didn't start as a roadmap, it started as an experiment, one carefully-structured prompt to Claude Fable 5 while it was briefly available. What came back genuinely stopped me. Not a toy or a snippet, but a coherent, architecturally sound foundation, a real engine, the plugin seam, scripting wired in. It even generated little demo videos of itself running. So I kept building.
The parts I'm most proud of now:
• Percentiles you can actually trust, HDR histograms merged across threads, so p99.9 is real, not sampled.
• Scenarios in plain YAML, with embedded JavaScript (per-VU on QuickJS) when you need real logic.
• Protocols and datastores as installable plugins, so the core binary stays small.
• A live web UI baked into the binary, a desktop app, a drop-in CI gate, and observe, which pulls your server's Prometheus metrics after a run and lines them up against your latency timeline, so "p95 spiked" meets "the DB hit 90% CPU".
Honest caveats: it's source-available under Elastic-2.0 (not OSI open source), and still beta, HTTP/gRPC are rock solid, the browser-driven path is newer.
What genuinely excites me isn't "AI wrote it", it's how far one well-structured prompt got on a real systems-architecture problem. The gap between an idea and working code is closing faster than I expected.
Happy to go deep on any of it, the QuickJS-per-VU design, the HDR merge, even the original prompt. And I'd love to know: what would make loadr a daily driver for you?
Try it: https://loadr.io · Demos: https://loadr.io/demos/
No comment highlights available yet. Please check back later!
About loadr on Product Hunt
“Find the breaking point — load testing in one Rust binary”
loadr was submitted on Product Hunt and earned 5 upvotes and 1 comments, placing #159 on the daily leaderboard. One prompt. While Claude Fable 5 was briefly available, we asked it to build a load tester in Rust that combined the best of k6, JMeter, Gatling and Locust — plugins, embedded scripting, distributed execution. It returned a real foundation, not a toy. We kept building. Today it's one Rust binary with declarative YAML + JavaScript tests, exact percentiles (HDR histograms — p99.9 is real, not sampled), installable protocol/datastore plugins, a live web UI, distributed agent runs and a CI gate.
loadr was featured in Software Engineering (42.7k followers), Developer Tools (515.4k followers) and GitHub (41.3k followers) on Product Hunt. Together, these topics include over 106.4k products, making this a competitive space to launch in.
Who hunted loadr ?
loadr was hunted by Andrew Rea. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
Want to see how loadr stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.