[camel_gopher]

Nearly all time series databases store single value aggregations (think p95) over a time period. A select few store actual serialized distributions (Atlas from Netflix, Apica IronDB, some bespoke implementations). Latency tooling is sorely overlooked mostly because the good tooling is complex, and requires corresponding visualization tooling. Most of the vendors have some implementation of heat map or histogram visualization but either the math is wrong or the UI can’t handle a non trivial volume of samples. Unfortunately it’s been a race to the bottom for latency measurement tooling, with the users losing.

Source: I’ve done this a lot

[Fripplebubby]

I take it as a given that what is stored and graphed is an information-destroying aggregate, but I think that aggregate is actually still useful + meaningful

[camel_gopher]

Someone smart I know coined it as “wrong but useful”