On Mon, 2023-03-13 at 12:24 -0400, Harrison Borges wrote: > I’m running into severe performance problems with Postgres as I increase the > number > of concurrent requests against my backend. I’ve identified that the > bottleneck is > Postgres, and to simplify the test case, I created an endpoint that only does > a > count query on a table with ~500k rows. At 5 concurrent users, the response > time > was 33ms, at 10 users it was 60ms, and at 20 users it was 120ms. > > As the number of concurrent users increases, the response time for the count > query > also increases significantly, indicating that Postgres may not be scaling > well to > handle the increasing load. > > This manifests in essentially a server meltdown on production. As the > concurrent > requests stack up, our server is stuck waiting for more and more queries. > Eventually requests begin timing out as they start taking over 30 seconds to > respond. > > Am I doing something obviously wrong? Does this sound like normal behavior?
That sounds like quite normal and expected behavior. A query that counts the number of rows in a table of half a million rows is quite expensive and keeps a CPU core busy for a while (provided everything is cached). At some degree of parallelism, your CPU is overloaded, which leads to non-linear slowdown. The thing you are doing wrong is that you are putting too much load on this system. Yours, Laurenz Albe
