Credits & influences

loadr stands on the shoulders of the load-testing tools that came before it. It is not a fork of any of them — it's a fresh implementation in Rust — but its design borrows the best ideas from four projects, deliberately and gratefully.

k6 — the model

loadr independently implements the modern load-testing execution model that k6 helped popularize: the seven executor types (constant-vus, ramping-vus, constant-arrival-rate, ramping-arrival-rate, per-vu-iterations, shared-iterations, externally-controlled), the open/closed load distinction, four metric types (Counter, Gauge, Rate, Trend), thresholds as pass/fail gates with abortOnFail and exit code 99, checks, groups and tags. It is a fresh Rust implementation — not a fork or a port, and no k6 source is used. For teams moving across, loadr convert imports existing k6 scripts and the JS runtime accepts their imports so they run unchanged.

Apache JMeter — the arsenal

JMeter's breadth of assertions, extractors and timers shaped loadr's request toolkit: response/duration/size/JSONPath/XPath assertions, the regular expression / boundary / CSS / XPath extractors, the constant / uniform / gaussian timers and the constant-throughput timer (loadr's pacing), CSV data sets with shared/per-thread cursors and recycle/stop-at-EOF, and cookie management. loadr convert reads .jmx plans so you can bring decades of existing tests with you.

Gatling — the DSL

Gatling contributed the flow control and injection vocabulary: the repeat / while / if-else loops and conditionals, the randomSwitch / uniformRandomSwitch / roundRobinSwitch branch selection (loadr's random step), the feeder strategies (sequential / random / shuffle), JSON feeders, and the request-rate throttle (reachRps). Gatling's rich, assertion-driven simulation reports also informed loadr's HTML report.

Locust — the behaviour model

Locust's weighted-task model — users that pick @task(weight) actions at random rather than running a fixed script — is exactly what loadr's weighted random step expresses. Locust's clean real-time web UI was a direct inspiration for loadr's built-in management UI, and its straightforward distributed master/worker model informed loadr's controller/agent design.

What loadr adds

The combination is the point — everything you would reach for k6, JMeter, Gatling or Locust to do — scriptable execution and a deep assertion arsenal and a flow-control DSL and weighted-behaviour modelling — in one binary, plus a few things none of them ship together: a single static binary with no runtime (no JVM, no Python, no Go toolchain, no protoc, no OpenSSL); mathematically correct distributed percentiles via HDR-histogram merging (not averaging); a sandboxed WASM + native plugin system that needs no rebuild; six protocols with per-phase timings; and a declarative, schema-validated YAML format you can code-review.

Trademarks and project names belong to their respective owners. loadr is an independent project and is not affiliated with or endorsed by k6/Grafana Labs, the Apache Software Foundation, Gatling Corp, or the Locust project.