[aseipp]

Dividing the fleet QPS by the number of nodes is completely meaningless because it assumes that queries are distributed evenly across every part of the system and that every part of the system is uniform (e.g. it is unclear what the read/write patterns are, proportion of these nodes are read replicas or hot standbys, if their sizing and configuration are the same). That isn't realistic at all. I would guess it is extremely likely that hot subsets of these clusters, depending on the use case, see anywhere from 1 to 4 orders of magnitude higher QPS than your guess, probably on a near constant basis.

Don't get me wrong, a lot of people have talked about Uber doing overengineering in weird ways, maybe they're even completely right. But being like "Well, obviously x/y = z, and z is rather small, therefore it's not impressive, isn't this obvious?" is the computer programming equivalent of the "econ 101 student says supply and demand explain everything" phenomenon. It's not an accurate characterization of the system at all and falls prey to the very thing you're alluding to ("this is obvious.")

[0cf8612b2e1e]

Simple enough just to think about localities and time of day. New York during Tuesday rush hour could be more load than all of North Dakota sees in a month. Even busy cities probably drop down to nothing on a weekday at 3am.