It's the more subtle instances of this that always are the most worrying to me, to be honest.

Imagine you have a data pipeline that spans multiple hosts, and you want telemetry on when an entity passes through each step? Suddenly you have to start caring about clock alignment in an order of magnitude comparable with network transit/computation time (microseconds) and that level of skew happens VERY often. There are certainly ways around this in how you build your system, but it's something that _must_ be considered and I find often isn't.

If you're monitoring other system metrics, and your application is time-dependent, you should be monitoring system time and ntpd stats as well.

/u/devnull42 is doing it right: https://news.ycombinator.com/item?id=11075883

For critical time dependent systems, I absolutely agree. I was unclear in that I was referring to far more mundane issues where slight skew can be problematic. I've seen telemetry systems in which the aformentioned deltas would be computed by doing a timedelta() on the recorded timestamp from each machine. With even subsecond skew, you can get some really interesting artifacts; negative durations, that sort of thing.

I run some pretty large NTP deployments and our NTP drift is never really over 1 second. Now the difference between NTP serverside drift and client server-side "skew" isn’t something I have looks at but for the most part I get a nagios alert on anything over 1 second of drift with 5 seconds being the most I have ever seen.

Can you share more detail as to how you would alert on drift? What acts as the canonical source?

Not sure how you'd configure it, but you don't actually need a canonical source. You just compare it against all/many other servers and look at the difference. If there's any real skew you need to look at all of them that had a difference then but you don't need a canonical source anymore.