It turns out that looping_call does check the deferred returned by its
callback, and (at least in the case of client_ips), we were relying on this,
and I broke it in #3604.
Update run_as_background_process to return the deferred, and make sure we
return it to clock.looping_call.
This introduces a mechanism for tracking resource usage by background
processes, along with an example of how it will be used.
This will help address #3518, but more importantly will give us better insights
into things which are happening but not being shown up by the request metrics.
We *could* do this with Measure blocks, but:
- I think having them pulled out as a completely separate metric class will
make it easier to distinguish top-level processes from those which are
nested.
- I want to be able to report on in-flight background processes, and I don't
think we want to do this for *all* Measure blocks.
PyPy's incminimark GC can't be triggered manually. From what I observed
there are no obvious issues with just letting it run normally. And
unlike CPython, it actually returns unused RAM to the system.
Signed-off-by: Vincent Breitmoser <look@my.amazin.horse>
It's useful to know when there are peaks in incoming requests - which isn't
quite the same as there being peaks in outgoing responses, due to the time
taken to handle requests.
Prometheus handles all metrics as floats, and sometimes we store non-integer
values in them (notably, durations in seconds), so let's render them as floats
too.
(Note that the standard client libraries also treat Counters as floats.)
