[otterley]

The column in the table claiming the "number of page loads that would experience the 99th %ile" is mathematically suspect. It directly contradicts what a percentile is.

By definition, at 99th percentile, if I have 100 page loads, the one with the worst latency would be over the 99th percentile. That's not 85.2%, 87.1%, 67.6%, etc. The formula shown in that column makes no sense at all.

[tpankaj]

That's not what that column is supposed to mean afaict. The way I read it is it's showing that if the website requires hundreds of different parallel backend service calls to serve the page load, what's the probability a page load hits the p99 instrumentation latency?

We have a similar chart at my job to illustrate the point that high p99 latency on a backend service doesn't mean only 1% of end-user page loads are affected.

[otterley]

Ah, I see. So, for example, if one page request would result in 190 different backend requests to fulfill, then the possibility that at least one of those subrequests exceeds the 99th percentile would be 85.2%. That makes a lot more sense.

[edenfed]

I recommend watching Gil Tene’s talk, I think he explains the math better than I do: https://www.youtube.com/watch?v=lJ8ydIuPFeU

[bjt12345]

But what if the 100 page loads are just a sample of the population?