Demos & training

Watch loadr work.

Ten short sessions, from your first test to flow control, feeders, distributed fleets and the live UI. Every clip is a real recording of the actual binary against a live server — what you see is what you get. Follow them in order as a getting-started course, or jump to the feature you need.

01

The quickstart 0:24

A complete load test in 20 lines of YAML: validate it, run it, read the summary.

  • ▸ the scenarios / flow / thresholds structure
  • ▸ loadr validate before you burn a test run
  • ▸ live progress, then the k6-style summary
  • ▸ checks, latency percentiles and green thresholds

Docs: Your first test

02

Validation that respects you 0:16

Broken test in, precise diagnostics out — before a single request is sent.

  • ▸ line & column on every finding
  • ▸ did-you-mean fixes for typos
  • ▸ executor parameter checks
  • ▸ undefined-variable detection

Docs: loadr validate

03

Data, extraction & JS in one flow 0:18

The correlation workflow every real test needs.

  • ▸ CSV rows feeding each login
  • ▸ JSONPath-extracted token replayed via ${token}
  • ▸ inline ${js: crypto.uuidv4()}
  • ▸ custom metrics with exact-count thresholds

Docs: Extraction · Data · JavaScript

04

Thresholds gate your CI 0:20

What failure looks like — and how it reaches your pipeline and your team.

  • ▸ an SLO the endpoint can't meet
  • ▸ red ✗ thresholds, exit=99
  • ▸ --summary-export for machines
  • ▸ loadr report HTML for humans

Docs: Thresholds · Exit codes

05

Escape JMeter. Import k6. 0:21

Bring your existing test estate with you.

  • ▸ a JMeter .jmx plan → clean YAML
  • ▸ warnings name exactly what to review
  • ▸ a k6 script with scenarios → same
  • ▸ converted output always validates

Docs: From JMeter · From k6

06

A distributed fleet, live 0:34

Controller, agents, exact partitioning and merged percentiles — in 30 seconds.

  • ▸ loadr controller + two joining agents
  • ▸ fleet health from the API
  • ▸ 400 iterations split exactly in two
  • ▸ HDR-merged, fleet-wide percentiles

Docs: Distributed testing · Metric aggregation

07

Flow control & weighted tasks 0:23

Loops, conditionals and weighted branches — Gatling's DSL and Locust's task model in YAML.

  • ▸ while loop: browse a random number of pages
  • ▸ weighted random: 70% browse / 25% cart / 5% checkout
  • ▸ repeat and if/else for retries
  • ▸ realistic user journeys, no scripting required

Docs: Flow control

08

Feeders & throttling 0:21

Random data feeders and a hard request-rate ceiling — Gatling's feeders and reachRps.

  • ▸ a random feeder picking SKUs
  • ▸ 20 VUs, but throttle caps the scenario at 30 req/s
  • ▸ the observed rate holds at the ceiling
  • ▸ stay under a known rate limit, on any executor

Docs: Feeders & throttling

09

The live web UI 0:42

A real browser session during a 30-VU run.

  • ▸ live RPS, VU and percentile charts (SSE)
  • ▸ threshold PASS pills updating in real time
  • ▸ run page with Stop / Kill / Pause controls
  • ▸ test editor, agents view, dark mode native

Docs: The management UI

10

The agent fleet, in the UI 0:37

A controller with three live agents, managed from the browser — the distributed run from #6, seen through the web UI.

  • ▸ the fleet view: three healthy agents, live
  • ▸ 30 VUs partitioned exactly 10 / 10 / 10
  • ▸ per-agent cores, labels and heartbeat
  • ▸ the overview shows centrally-merged percentiles

Docs: Controller & agents

Ready to run it yourself?

Everything in these demos ships in the binary, and the repo includes 15 runnable examples covering every feature shown here — and the ones we didn't fit in.

Get loadr Read the docs