Performance Workloads

Check whether the climb advances with work done or with elapsed time. Replot it against cumulative completed work, run a low-rate control, probe a path the run never writes to, and restart the process keeping its data.

Start at the size the system would reach under baseline demand, never pre-raised to peak, and timestamp two series: offered demand and capacity actually serving. The interval between them is the exposure window, and what happened inside it is the result.

Tag every submitted unit with a unique identifier before demand rises, then reconcile after the observation window: submitted equals completed plus refused plus pending. Separately compare distinct completed identifiers against total completions, because totals alone hide loss and repetition together.

Derive the transaction mix, arrival shape and data profile from observed traffic rather than opinion, state the reference period, and keep the model a versioned, owned artefact that is re-derived on a schedule instead of ageing into fiction.

It is legitimate when the shift in level has an identified, intentional cause, was reproduced across repeats, and still meets the obligation the team owes. It is a moved goalpost when the reason is that meeting the old figure became inconvenient.

Vary overlap alone. Run the same arrival rate with few busy clients and then with many idle ones: if duration differs, overlap is the cause. Repeat with requests spread across distinct records to locate what is shared.

Only checks cheap enough to fit inside the applying side's own budget: a length floor, a required field, a marker. Deep parsing per reply steals the capacity that generates demand, so sample it instead and report what share was verified.

The read-out locates the bucket holding the ranked request, not its time, so the figure carries that bucket's width as uncertainty. Interpolating inside assumes a spread the slow end does not have, and an unbounded top bucket reports nothing at all.

Decide from what the hold must prove. Arrange the run to hit periodic work - scheduled jobs, credential rotation, cache expiry, index maintenance - when that interaction is the risk; otherwise disable it and record that the trend excludes it.

Compare what the load generator offered against what the service received: the offered rate is known and unchanged, so any excess was manufactured inside the system. Repeats of identifiers already submitted, arriving synchronised at a fixed delay, confirm it.