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- # Copyright 2015, 2016 OpenMarket Ltd
- # Copyright 2022 The Matrix.org Foundation C.I.C.
- #
- # 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 itertools
- import logging
- import os
- import platform
- import threading
- from typing import (
- Callable,
- Dict,
- Generic,
- Iterable,
- Mapping,
- Optional,
- Sequence,
- Set,
- Tuple,
- Type,
- TypeVar,
- Union,
- cast,
- )
- import attr
- from prometheus_client import CollectorRegistry, Counter, Gauge, Histogram, Metric
- from prometheus_client.core import (
- REGISTRY,
- GaugeHistogramMetricFamily,
- GaugeMetricFamily,
- )
- from twisted.python.threadpool import ThreadPool
- # This module is imported for its side effects; flake8 needn't warn that it's unused.
- import synapse.metrics._reactor_metrics # noqa: F401
- from synapse.metrics._exposition import (
- MetricsResource,
- generate_latest,
- start_http_server,
- )
- from synapse.metrics._gc import MIN_TIME_BETWEEN_GCS, install_gc_manager
- from synapse.metrics._types import Collector
- from synapse.util import SYNAPSE_VERSION
- logger = logging.getLogger(__name__)
- METRICS_PREFIX = "/_synapse/metrics"
- all_gauges: Dict[str, Collector] = {}
- HAVE_PROC_SELF_STAT = os.path.exists("/proc/self/stat")
- class _RegistryProxy:
- @staticmethod
- def collect() -> Iterable[Metric]:
- for metric in REGISTRY.collect():
- if not metric.name.startswith("__"):
- yield metric
- # A little bit nasty, but collect() above is static so a Protocol doesn't work.
- # _RegistryProxy matches the signature of a CollectorRegistry instance enough
- # for it to be usable in the contexts in which we use it.
- # TODO Do something nicer about this.
- RegistryProxy = cast(CollectorRegistry, _RegistryProxy)
- @attr.s(slots=True, hash=True, auto_attribs=True)
- class LaterGauge(Collector):
- name: str
- desc: str
- labels: Optional[Sequence[str]] = attr.ib(hash=False)
- # callback: should either return a value (if there are no labels for this metric),
- # or dict mapping from a label tuple to a value
- caller: Callable[
- [], Union[Mapping[Tuple[str, ...], Union[int, float]], Union[int, float]]
- ]
- def collect(self) -> Iterable[Metric]:
- g = GaugeMetricFamily(self.name, self.desc, labels=self.labels)
- try:
- calls = self.caller()
- except Exception:
- logger.exception("Exception running callback for LaterGauge(%s)", self.name)
- yield g
- return
- if isinstance(calls, (int, float)):
- g.add_metric([], calls)
- else:
- for k, v in calls.items():
- g.add_metric(k, v)
- yield g
- def __attrs_post_init__(self) -> None:
- self._register()
- def _register(self) -> None:
- if self.name in all_gauges.keys():
- logger.warning("%s already registered, reregistering" % (self.name,))
- REGISTRY.unregister(all_gauges.pop(self.name))
- REGISTRY.register(self)
- all_gauges[self.name] = self
- # `MetricsEntry` only makes sense when it is a `Protocol`,
- # but `Protocol` can't be used as a `TypeVar` bound.
- MetricsEntry = TypeVar("MetricsEntry")
- class InFlightGauge(Generic[MetricsEntry], Collector):
- """Tracks number of things (e.g. requests, Measure blocks, etc) in flight
- at any given time.
- Each InFlightGauge will create a metric called `<name>_total` that counts
- the number of in flight blocks, as well as a metrics for each item in the
- given `sub_metrics` as `<name>_<sub_metric>` which will get updated by the
- callbacks.
- Args:
- name
- desc
- labels
- sub_metrics: A list of sub metrics that the callbacks will update.
- """
- def __init__(
- self,
- name: str,
- desc: str,
- labels: Sequence[str],
- sub_metrics: Sequence[str],
- ):
- self.name = name
- self.desc = desc
- self.labels = labels
- self.sub_metrics = sub_metrics
- # Create a class which have the sub_metrics values as attributes, which
- # default to 0 on initialization. Used to pass to registered callbacks.
- self._metrics_class: Type[MetricsEntry] = attr.make_class(
- "_MetricsEntry",
- attrs={x: attr.ib(default=0) for x in sub_metrics},
- slots=True,
- )
- # Counts number of in flight blocks for a given set of label values
- self._registrations: Dict[
- Tuple[str, ...], Set[Callable[[MetricsEntry], None]]
- ] = {}
- # Protects access to _registrations
- self._lock = threading.Lock()
- self._register_with_collector()
- def register(
- self,
- key: Tuple[str, ...],
- callback: Callable[[MetricsEntry], None],
- ) -> None:
- """Registers that we've entered a new block with labels `key`.
- `callback` gets called each time the metrics are collected. The same
- value must also be given to `unregister`.
- `callback` gets called with an object that has an attribute per
- sub_metric, which should be updated with the necessary values. Note that
- the metrics object is shared between all callbacks registered with the
- same key.
- Note that `callback` may be called on a separate thread.
- """
- with self._lock:
- self._registrations.setdefault(key, set()).add(callback)
- def unregister(
- self,
- key: Tuple[str, ...],
- callback: Callable[[MetricsEntry], None],
- ) -> None:
- """Registers that we've exited a block with labels `key`."""
- with self._lock:
- self._registrations.setdefault(key, set()).discard(callback)
- def collect(self) -> Iterable[Metric]:
- """Called by prometheus client when it reads metrics.
- Note: may be called by a separate thread.
- """
- in_flight = GaugeMetricFamily(
- self.name + "_total", self.desc, labels=self.labels
- )
- metrics_by_key = {}
- # We copy so that we don't mutate the list while iterating
- with self._lock:
- keys = list(self._registrations)
- for key in keys:
- with self._lock:
- callbacks = set(self._registrations[key])
- in_flight.add_metric(key, len(callbacks))
- metrics = self._metrics_class()
- metrics_by_key[key] = metrics
- for callback in callbacks:
- callback(metrics)
- yield in_flight
- for name in self.sub_metrics:
- gauge = GaugeMetricFamily(
- "_".join([self.name, name]), "", labels=self.labels
- )
- for key, metrics in metrics_by_key.items():
- gauge.add_metric(key, getattr(metrics, name))
- yield gauge
- def _register_with_collector(self) -> None:
- if self.name in all_gauges.keys():
- logger.warning("%s already registered, reregistering" % (self.name,))
- REGISTRY.unregister(all_gauges.pop(self.name))
- REGISTRY.register(self)
- all_gauges[self.name] = self
- class GaugeBucketCollector(Collector):
- """Like a Histogram, but the buckets are Gauges which are updated atomically.
- The data is updated by calling `update_data` with an iterable of measurements.
- We assume that the data is updated less frequently than it is reported to
- Prometheus, and optimise for that case.
- """
- __slots__ = (
- "_name",
- "_documentation",
- "_bucket_bounds",
- "_metric",
- )
- def __init__(
- self,
- name: str,
- documentation: str,
- buckets: Iterable[float],
- registry: CollectorRegistry = REGISTRY,
- ):
- """
- Args:
- name: base name of metric to be exported to Prometheus. (a _bucket suffix
- will be added.)
- documentation: help text for the metric
- buckets: The top bounds of the buckets to report
- registry: metric registry to register with
- """
- self._name = name
- self._documentation = documentation
- # the tops of the buckets
- self._bucket_bounds = [float(b) for b in buckets]
- if self._bucket_bounds != sorted(self._bucket_bounds):
- raise ValueError("Buckets not in sorted order")
- if self._bucket_bounds[-1] != float("inf"):
- self._bucket_bounds.append(float("inf"))
- # We initially set this to None. We won't report metrics until
- # this has been initialised after a successful data update
- self._metric: Optional[GaugeHistogramMetricFamily] = None
- registry.register(self)
- def collect(self) -> Iterable[Metric]:
- # Don't report metrics unless we've already collected some data
- if self._metric is not None:
- yield self._metric
- def update_data(self, values: Iterable[float]) -> None:
- """Update the data to be reported by the metric
- The existing data is cleared, and each measurement in the input is assigned
- to the relevant bucket.
- """
- self._metric = self._values_to_metric(values)
- def _values_to_metric(self, values: Iterable[float]) -> GaugeHistogramMetricFamily:
- total = 0.0
- bucket_values = [0 for _ in self._bucket_bounds]
- for v in values:
- # assign each value to a bucket
- for i, bound in enumerate(self._bucket_bounds):
- if v <= bound:
- bucket_values[i] += 1
- break
- # ... and increment the sum
- total += v
- # now, aggregate the bucket values so that they count the number of entries in
- # that bucket or below.
- accumulated_values = itertools.accumulate(bucket_values)
- return GaugeHistogramMetricFamily(
- self._name,
- self._documentation,
- buckets=list(
- zip((str(b) for b in self._bucket_bounds), accumulated_values)
- ),
- gsum_value=total,
- )
- #
- # Detailed CPU metrics
- #
- class CPUMetrics(Collector):
- def __init__(self) -> None:
- ticks_per_sec = 100
- try:
- # Try and get the system config
- ticks_per_sec = os.sysconf("SC_CLK_TCK")
- except (ValueError, TypeError, AttributeError):
- pass
- self.ticks_per_sec = ticks_per_sec
- def collect(self) -> Iterable[Metric]:
- if not HAVE_PROC_SELF_STAT:
- return
- with open("/proc/self/stat") as s:
- line = s.read()
- raw_stats = line.split(") ", 1)[1].split(" ")
- user = GaugeMetricFamily("process_cpu_user_seconds_total", "")
- user.add_metric([], float(raw_stats[11]) / self.ticks_per_sec)
- yield user
- sys = GaugeMetricFamily("process_cpu_system_seconds_total", "")
- sys.add_metric([], float(raw_stats[12]) / self.ticks_per_sec)
- yield sys
- REGISTRY.register(CPUMetrics())
- #
- # Federation Metrics
- #
- sent_transactions_counter = Counter("synapse_federation_client_sent_transactions", "")
- events_processed_counter = Counter("synapse_federation_client_events_processed", "")
- event_processing_loop_counter = Counter(
- "synapse_event_processing_loop_count", "Event processing loop iterations", ["name"]
- )
- event_processing_loop_room_count = Counter(
- "synapse_event_processing_loop_room_count",
- "Rooms seen per event processing loop iteration",
- ["name"],
- )
- # Used to track where various components have processed in the event stream,
- # e.g. federation sending, appservice sending, etc.
- event_processing_positions = Gauge("synapse_event_processing_positions", "", ["name"])
- # Used to track the current max events stream position
- event_persisted_position = Gauge("synapse_event_persisted_position", "")
- # Used to track the received_ts of the last event processed by various
- # components
- event_processing_last_ts = Gauge("synapse_event_processing_last_ts", "", ["name"])
- # Used to track the lag processing events. This is the time difference
- # between the last processed event's received_ts and the time it was
- # finished being processed.
- event_processing_lag = Gauge("synapse_event_processing_lag", "", ["name"])
- event_processing_lag_by_event = Histogram(
- "synapse_event_processing_lag_by_event",
- "Time between an event being persisted and it being queued up to be sent to the relevant remote servers",
- ["name"],
- )
- # Build info of the running server.
- build_info = Gauge(
- "synapse_build_info", "Build information", ["pythonversion", "version", "osversion"]
- )
- build_info.labels(
- " ".join([platform.python_implementation(), platform.python_version()]),
- SYNAPSE_VERSION,
- " ".join([platform.system(), platform.release()]),
- ).set(1)
- # 3PID send info
- threepid_send_requests = Histogram(
- "synapse_threepid_send_requests_with_tries",
- documentation="Number of requests for a 3pid token by try count. Note if"
- " there is a request with try count of 4, then there would have been one"
- " each for 1, 2 and 3",
- buckets=(1, 2, 3, 4, 5, 10),
- labelnames=("type", "reason"),
- )
- threadpool_total_threads = Gauge(
- "synapse_threadpool_total_threads",
- "Total number of threads currently in the threadpool",
- ["name"],
- )
- threadpool_total_working_threads = Gauge(
- "synapse_threadpool_working_threads",
- "Number of threads currently working in the threadpool",
- ["name"],
- )
- threadpool_total_min_threads = Gauge(
- "synapse_threadpool_min_threads",
- "Minimum number of threads configured in the threadpool",
- ["name"],
- )
- threadpool_total_max_threads = Gauge(
- "synapse_threadpool_max_threads",
- "Maximum number of threads configured in the threadpool",
- ["name"],
- )
- def register_threadpool(name: str, threadpool: ThreadPool) -> None:
- """Add metrics for the threadpool."""
- threadpool_total_min_threads.labels(name).set(threadpool.min)
- threadpool_total_max_threads.labels(name).set(threadpool.max)
- threadpool_total_threads.labels(name).set_function(lambda: len(threadpool.threads))
- threadpool_total_working_threads.labels(name).set_function(
- lambda: len(threadpool.working)
- )
- __all__ = [
- "Collector",
- "MetricsResource",
- "generate_latest",
- "start_http_server",
- "LaterGauge",
- "InFlightGauge",
- "GaugeBucketCollector",
- "MIN_TIME_BETWEEN_GCS",
- "install_gc_manager",
- ]
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