anonymousland-synapse/synapse/metrics/background_process_metrics.py
Richard van der Hoff 6e3fc657b4 Resource tracking for background processes
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.
2018-07-18 10:50:33 +01:00

180 lines
6.1 KiB
Python

# -*- coding: utf-8 -*-
# Copyright 2018 New Vector Ltd
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import six
from prometheus_client.core import REGISTRY, Counter, GaugeMetricFamily
from twisted.internet import defer
from synapse.util.logcontext import LoggingContext, PreserveLoggingContext
_background_process_start_count = Counter(
"synapse_background_process_start_count",
"Number of background processes started",
["name"],
)
# we set registry=None in all of these to stop them getting registered with
# the default registry. Instead we collect them all via the CustomCollector,
# which ensures that we can update them before they are collected.
#
_background_process_ru_utime = Counter(
"synapse_background_process_ru_utime_seconds",
"User CPU time used by background processes, in seconds",
["name"],
registry=None,
)
_background_process_ru_stime = Counter(
"synapse_background_process_ru_stime_seconds",
"System CPU time used by background processes, in seconds",
["name"],
registry=None,
)
_background_process_db_txn_count = Counter(
"synapse_background_process_db_txn_count",
"Number of database transactions done by background processes",
["name"],
registry=None,
)
_background_process_db_txn_duration = Counter(
"synapse_background_process_db_txn_duration_seconds",
("Seconds spent by background processes waiting for database "
"transactions, excluding scheduling time"),
["name"],
registry=None,
)
_background_process_db_sched_duration = Counter(
"synapse_background_process_db_sched_duration_seconds",
"Seconds spent by background processes waiting for database connections",
["name"],
registry=None,
)
# map from description to a counter, so that we can name our logcontexts
# incrementally. (It actually duplicates _background_process_start_count, but
# it's much simpler to do so than to try to combine them.)
_background_process_counts = dict() # type: dict[str, int]
# map from description to the currently running background processes.
#
# it's kept as a dict of sets rather than a big set so that we can keep track
# of process descriptions that no longer have any active processes.
_background_processes = dict() # type: dict[str, set[_BackgroundProcess]]
class _Collector(object):
"""A custom metrics collector for the background process metrics.
Ensures that all of the metrics are up-to-date with any in-flight processes
before they are returned.
"""
def collect(self):
background_process_in_flight_count = GaugeMetricFamily(
"synapse_background_process_in_flight_count",
"Number of background processes in flight",
labels=["name"],
)
for desc, processes in six.iteritems(_background_processes):
background_process_in_flight_count.add_metric(
(desc,), len(processes),
)
for process in processes:
process.update_metrics()
yield background_process_in_flight_count
# now we need to run collect() over each of the static Counters, and
# yield each metric they return.
for m in (
_background_process_ru_utime,
_background_process_ru_stime,
_background_process_db_txn_count,
_background_process_db_txn_duration,
_background_process_db_sched_duration,
):
for r in m.collect():
yield r
REGISTRY.register(_Collector())
class _BackgroundProcess(object):
def __init__(self, desc, ctx):
self.desc = desc
self._context = ctx
self._reported_stats = None
def update_metrics(self):
"""Updates the metrics with values from this process."""
new_stats = self._context.get_resource_usage()
if self._reported_stats is None:
diff = new_stats
else:
diff = new_stats - self._reported_stats
self._reported_stats = new_stats
_background_process_ru_utime.labels(self.desc).inc(diff.ru_utime)
_background_process_ru_stime.labels(self.desc).inc(diff.ru_stime)
_background_process_db_txn_count.labels(self.desc).inc(
diff.db_txn_count,
)
_background_process_db_txn_duration.labels(self.desc).inc(
diff.db_txn_duration_sec,
)
_background_process_db_sched_duration.labels(self.desc).inc(
diff.db_sched_duration_sec,
)
def run_as_background_process(desc, func, *args, **kwargs):
"""Run the given function in its own logcontext, with resource metrics
This should be used to wrap processes which are fired off to run in the
background, instead of being associated with a particular request.
Args:
desc (str): a description for this background process type
func: a function, which may return a Deferred
args: positional args for func
kwargs: keyword args for func
Returns: None
"""
@defer.inlineCallbacks
def run():
count = _background_process_counts.get(desc, 0)
_background_process_counts[desc] = count + 1
_background_process_start_count.labels(desc).inc()
with LoggingContext(desc) as context:
context.request = "%s-%i" % (desc, count)
proc = _BackgroundProcess(desc, context)
_background_processes.setdefault(desc, set()).add(proc)
try:
yield func(*args, **kwargs)
finally:
proc.update_metrics()
_background_processes[desc].remove(proc)
with PreserveLoggingContext():
run()