We are migrating telemetry backend from legacy database to Prometheus and
require estimating percentiles on gauge metrics published by user
applications. Estimating percentiles on a gauge metric in Prometheus is not
feasible and for a number of reasons, client applications will be difficult
to modify to start publishing histograms.
I am exploring feasibility of creating a histogram in a recording rule in
Prometheus based on the metrics published by users. The partial work put in
so far seems inefficient, also illegible. Is there a recommended approach
to solve this problem? As stated earlier, it will be extremely hard to
solve the problem on the client side and I am looking for a solution within
Prometheus.
*Current metric is a gauge with with values representing request latency.*
http_duration_milliseconds_gauge{instance="instance1:port1"}[1h]
1659752188 100
1659752068 120
..
1659751708 150
1659751588 160
*Desired histogram after conversion -*
http_duration_milliseconds_hist_bucket{instance="instance1:port1", le=100}
133
http_duration_milliseconds_hist_bucket{instance="instance1:port1", le=120}
222
http_duration_milliseconds_hist_bucket{instance="instance1:port1", le=140}
311
http_duration_milliseconds_hist_bucket{instance="instance1:port1", le=160}
330
http_duration_milliseconds_hist_bucket{instance="instance1:port1", le=180}
339
http_duration_milliseconds_hist_bucket{instance="instance1:port1", le=200}
340
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