I would add always (for network servers) run “open” loads tests with each request being independent of the fates of the other requests, probably from a Poisson

I would add always (for network servers) run “open” loads tests with each request being independent of the fates of the other requests, probably from a Poisson distribution (generated by having the delays be pulled from exponential random distribution ( https://en.wikipedia.org/wiki/Exponential_distribution https://en.wikipedia.org/wiki/Exponential_distribution ). So many load tools send a request then wait for the reply then send the next. That is basically useless for understanding variance under spiky load and for assessing when a system is below its capacity how stable it is. For real world performance, the variance matters a lot. The code will make some things be cached some not (so the data variability in the test load should follow the same sort of power law that your real traffic does), and even if you get 10% faster at the median if the variance goes up the quality is lower.