[cortesoft]

Some of this is good, but the idea that you can determine your likelihood of experiencing a 99th percentile latency on a webpage by the naive probability calculation shown (1 - .99^n where n is the number of objects requested on a page) is silly. That is assuming that latency is completely randomly distributed across all objects and all clients to a page.

This is completely not true. Latency is very dependent on the client requesting and the object being requested. You are going to get clustering, not an even distribution.

[JaRail]

+1. The majority of those requests on major websites don't matter. They are optional elements/scripts and prefetches for possible actions.

Now, if the point is that something will be delayed, that's true. And it's true that many people don't realize that. There's the classic example where if everyone tries to be five minutes early, your group is still going to be late.

The real lesson is to analyse your critical path to death and ensure it is as resilient as possible. And if possible, real data is buckets more meaningful than conventional load tests.

I also don't see anything in here about how to get meaningful metrics from real users. The W3C Navigation Timing API has really shed a ton of light into things commonly forgotten.