Estimate how much event traffic an experimentation pipeline can process and how many simultaneous experiments it can sustain. Compare worker throughput with incoming exposure and event rates while retaining configurable capacity headroom.
The main result is remaining event-processing throughput after the entered user load. Experiment capacity divides usable throughput by the expected event rate per experiment.
Benchmark the sustainable worker rate with representative payloads, storage latency, retries, and aggregation work.
12 workers at 1,500 events/s with 25% headroom provide 13,500 events/s. A 10,000 events/s incoming load leaves 3,500 events/s spare.
It uses the inputs, formula, units, and independence assumptions shown on this page. Change the inputs to match your own system or experiment.
Use representative averages for planning, preserve headroom where applicable, and test multiple plausible scenarios instead of relying on one point estimate.
No. The result is a planning estimate. Validate it with measured data, monitoring, load tests, or an experiment-design review as appropriate.
The calculator checks values required by the formula and displays an error instead of returning NaN or Infinity. Valid zero values remain available where they are meaningful.
Tools may use different statistical approximations, unit conventions, rounding rules, priors, confidence definitions, or operational headroom assumptions.
| Variable | Unit | Meaning |
|---|---|---|
| Raw throughput | events/s | Workers × measured worker rate |
| Headroom | percent | Capacity held for bursts and recovery |
| Usable throughput | events/s | Raw throughput after headroom |