On Tue, Sep 17, 2013 at 1:20 PM, Derek Balling <[email protected]> wrote:
> > On Sep 17, 2013, at 4:18 PM, [email protected] wrote: > > > On Tue, Sep 17, 2013 at 11:44:22AM -0400, Doug Hughes wrote: > >> Oh, and P95/P99 distributions (commonly used for billing by network > >> carriers on MPLS) > > > > If you're only paying attention to p95/p99 in relation to network you're > likely to be missing interesting and useful information. > > e.g. knowing that on average a user gets a page returned in 2 seconds is > great, but if your p95 is out in the 30 second region that's a number of > potentially unhappy users. > > I'd see the ideal goal as getting your mean as low as possible *and* > your p95/p99 as close to your mean as possible :) > > From my experience p95/p99 data is about consumption not > latency/performance metrics. There are a number people who look at web performance metrics with percentile latency metrics. Amazon is the most known big company that does this, but I know that Google definitely does this as well. Amazon talks about it as TP50, TP90, TP99, so on. TP for transaction percentile. Here's a nice blog post from 37signals on the "problem with averages" - http://37signals.com/svn/posts/1836-the-problem-with-averages Dana -- Dana Quinn [email protected]
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