diff options
Diffstat (limited to 'synapse')
| -rw-r--r-- | synapse/metrics/metric.py | 328 | ||||
| -rw-r--r-- | synapse/metrics/process_collector.py | 122 |
2 files changed, 0 insertions, 450 deletions
diff --git a/synapse/metrics/metric.py b/synapse/metrics/metric.py deleted file mode 100644 index f421e7a93f..0000000000 --- a/synapse/metrics/metric.py +++ /dev/null @@ -1,328 +0,0 @@ -# -*- coding: utf-8 -*- -# Copyright 2015, 2016 OpenMarket 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. - - -from itertools import chain -import logging -import re - -logger = logging.getLogger(__name__) - - -def flatten(items): - """Flatten a list of lists - - Args: - items: iterable[iterable[X]] - - Returns: - list[X]: flattened list - """ - return list(chain.from_iterable(items)) - - -class BaseMetric(object): - """Base class for metrics which report a single value per label set - """ - - def __init__(self, name, labels=[], alternative_names=[]): - """ - Args: - name (str): principal name for this metric - labels (list(str)): names of the labels which will be reported - for this metric - alternative_names (iterable(str)): list of alternative names for - this metric. This can be useful to provide a migration path - when renaming metrics. - """ - self._names = [name] + list(alternative_names) - self.labels = labels # OK not to clone as we never write it - - def dimension(self): - return len(self.labels) - - def is_scalar(self): - return not len(self.labels) - - def _render_labelvalue(self, value): - return '"%s"' % (_escape_label_value(value),) - - def _render_key(self, values): - if self.is_scalar(): - return "" - return "{%s}" % ( - ",".join(["%s=%s" % (k, self._render_labelvalue(v)) - for k, v in zip(self.labels, values)]) - ) - - def _render_for_labels(self, label_values, value): - """Render this metric for a single set of labels - - Args: - label_values (list[object]): values for each of the labels, - (which get stringified). - value: value of the metric at with these labels - - Returns: - iterable[str]: rendered metric - """ - rendered_labels = self._render_key(label_values) - return ( - "%s%s %.12g" % (name, rendered_labels, value) - for name in self._names - ) - - def render(self): - """Render this metric - - Each metric is rendered as: - - name{label1="val1",label2="val2"} value - - https://prometheus.io/docs/instrumenting/exposition_formats/#text-format-details - - Returns: - iterable[str]: rendered metrics - """ - raise NotImplementedError() - - -class CounterMetric(BaseMetric): - """The simplest kind of metric; one that stores a monotonically-increasing - value that counts events or running totals. - - Example use cases for Counters: - - Number of requests processed - - Number of items that were inserted into a queue - - Total amount of data that a system has processed - Counters can only go up (and be reset when the process restarts). - """ - - def __init__(self, *args, **kwargs): - super(CounterMetric, self).__init__(*args, **kwargs) - - # dict[list[str]]: value for each set of label values. the keys are the - # label values, in the same order as the labels in self.labels. - # - # (if the metric is a scalar, the (single) key is the empty tuple). - self.counts = {} - - # Scalar metrics are never empty - if self.is_scalar(): - self.counts[()] = 0. - - def inc_by(self, incr, *values): - if len(values) != self.dimension(): - raise ValueError( - "Expected as many values to inc() as labels (%d)" % (self.dimension()) - ) - - # TODO: should assert that the tag values are all strings - - if values not in self.counts: - self.counts[values] = incr - else: - self.counts[values] += incr - - def inc(self, *values): - self.inc_by(1, *values) - - def render(self): - return flatten( - self._render_for_labels(k, self.counts[k]) - for k in sorted(self.counts.keys()) - ) - - -class GaugeMetric(BaseMetric): - """A metric that can go up or down - """ - - def __init__(self, *args, **kwargs): - super(GaugeMetric, self).__init__(*args, **kwargs) - - # dict[list[str]]: value for each set of label values. the keys are the - # label values, in the same order as the labels in self.labels. - # - # (if the metric is a scalar, the (single) key is the empty tuple). - self.guages = {} - - def set(self, v, *values): - if len(values) != self.dimension(): - raise ValueError( - "Expected as many values to inc() as labels (%d)" % (self.dimension()) - ) - - # TODO: should assert that the tag values are all strings - - self.guages[values] = v - - def render(self): - return flatten( - self._render_for_labels(k, self.guages[k]) - for k in sorted(self.guages.keys()) - ) - - -class CallbackMetric(BaseMetric): - """A metric that returns the numeric value returned by a callback whenever - it is rendered. Typically this is used to implement gauges that yield the - size or other state of some in-memory object by actively querying it.""" - - def __init__(self, name, callback, labels=[]): - super(CallbackMetric, self).__init__(name, labels=labels) - - self.callback = callback - - def render(self): - try: - value = self.callback() - except Exception: - logger.exception("Failed to render %s", self.name) - return ["# FAILED to render " + self.name] - - if self.is_scalar(): - return list(self._render_for_labels([], value)) - - return flatten( - self._render_for_labels(k, value[k]) - for k in sorted(value.keys()) - ) - - -class DistributionMetric(object): - """A combination of an event counter and an accumulator, which counts - both the number of events and accumulates the total value. Typically this - could be used to keep track of method-running times, or other distributions - of values that occur in discrete occurances. - - TODO(paul): Try to export some heatmap-style stats? - """ - - def __init__(self, name, *args, **kwargs): - self.counts = CounterMetric(name + ":count", **kwargs) - self.totals = CounterMetric(name + ":total", **kwargs) - - def inc_by(self, inc, *values): - self.counts.inc(*values) - self.totals.inc_by(inc, *values) - - def render(self): - return self.counts.render() + self.totals.render() - - -class CacheMetric(object): - __slots__ = ( - "name", "cache_name", "hits", "misses", "evicted_size", "size_callback", - ) - - def __init__(self, name, size_callback, cache_name): - self.name = name - self.cache_name = cache_name - - self.hits = 0 - self.misses = 0 - self.evicted_size = 0 - - self.size_callback = size_callback - - def inc_hits(self): - self.hits += 1 - - def inc_misses(self): - self.misses += 1 - - def inc_evictions(self, size=1): - self.evicted_size += size - - def render(self): - size = self.size_callback() - hits = self.hits - total = self.misses + self.hits - - return [ - """%s:hits{name="%s"} %d""" % (self.name, self.cache_name, hits), - """%s:total{name="%s"} %d""" % (self.name, self.cache_name, total), - """%s:size{name="%s"} %d""" % (self.name, self.cache_name, size), - """%s:evicted_size{name="%s"} %d""" % ( - self.name, self.cache_name, self.evicted_size - ), - ] - - -class MemoryUsageMetric(object): - """Keeps track of the current memory usage, using psutil. - - The class will keep the current min/max/sum/counts of rss over the last - WINDOW_SIZE_SEC, by polling UPDATE_HZ times per second - """ - - UPDATE_HZ = 2 # number of times to get memory per second - WINDOW_SIZE_SEC = 30 # the size of the window in seconds - - def __init__(self, hs, psutil): - clock = hs.get_clock() - self.memory_snapshots = [] - - self.process = psutil.Process() - - clock.looping_call(self._update_curr_values, 1000 / self.UPDATE_HZ) - - def _update_curr_values(self): - max_size = self.UPDATE_HZ * self.WINDOW_SIZE_SEC - self.memory_snapshots.append(self.process.memory_info().rss) - self.memory_snapshots[:] = self.memory_snapshots[-max_size:] - - def render(self): - if not self.memory_snapshots: - return [] - - max_rss = max(self.memory_snapshots) - min_rss = min(self.memory_snapshots) - sum_rss = sum(self.memory_snapshots) - len_rss = len(self.memory_snapshots) - - return [ - "process_psutil_rss:max %d" % max_rss, - "process_psutil_rss:min %d" % min_rss, - "process_psutil_rss:total %d" % sum_rss, - "process_psutil_rss:count %d" % len_rss, - ] - - -def _escape_character(m): - """Replaces a single character with its escape sequence. - - Args: - m (re.MatchObject): A match object whose first group is the single - character to replace - - Returns: - str - """ - c = m.group(1) - if c == "\\": - return "\\\\" - elif c == "\"": - return "\\\"" - elif c == "\n": - return "\\n" - return c - - -def _escape_label_value(value): - """Takes a label value and escapes quotes, newlines and backslashes - """ - return re.sub(r"([\n\"\\])", _escape_character, str(value)) diff --git a/synapse/metrics/process_collector.py b/synapse/metrics/process_collector.py deleted file mode 100644 index 6fec3de399..0000000000 --- a/synapse/metrics/process_collector.py +++ /dev/null @@ -1,122 +0,0 @@ -# -*- coding: utf-8 -*- -# Copyright 2015, 2016 OpenMarket 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 os - - -TICKS_PER_SEC = 100 -BYTES_PER_PAGE = 4096 - -HAVE_PROC_STAT = os.path.exists("/proc/stat") -HAVE_PROC_SELF_STAT = os.path.exists("/proc/self/stat") -HAVE_PROC_SELF_LIMITS = os.path.exists("/proc/self/limits") -HAVE_PROC_SELF_FD = os.path.exists("/proc/self/fd") - -# Field indexes from /proc/self/stat, taken from the proc(5) manpage -STAT_FIELDS = { - "utime": 14, - "stime": 15, - "starttime": 22, - "vsize": 23, - "rss": 24, -} - - -stats = {} - -# In order to report process_start_time_seconds we need to know the -# machine's boot time, because the value in /proc/self/stat is relative to -# this -boot_time = None -if HAVE_PROC_STAT: - with open("/proc/stat") as _procstat: - for line in _procstat: - if line.startswith("btime "): - boot_time = int(line.split()[1]) - - -def update_resource_metrics(): - if HAVE_PROC_SELF_STAT: - global stats - with open("/proc/self/stat") as s: - line = s.read() - # line is PID (command) more stats go here ... - raw_stats = line.split(") ", 1)[1].split(" ") - - for (name, index) in STAT_FIELDS.iteritems(): - # subtract 3 from the index, because proc(5) is 1-based, and - # we've lost the first two fields in PID and COMMAND above - stats[name] = int(raw_stats[index - 3]) - - -def _count_fds(): - # Not every OS will have a /proc/self/fd directory - if not HAVE_PROC_SELF_FD: - return 0 - - return len(os.listdir("/proc/self/fd")) - - -def register_process_collector(process_metrics): - process_metrics.register_collector(update_resource_metrics) - - if HAVE_PROC_SELF_STAT: - process_metrics.register_callback( - "cpu_user_seconds_total", - lambda: float(stats["utime"]) / TICKS_PER_SEC - ) - process_metrics.register_callback( - "cpu_system_seconds_total", - lambda: float(stats["stime"]) / TICKS_PER_SEC - ) - process_metrics.register_callback( - "cpu_seconds_total", - lambda: (float(stats["utime"] + stats["stime"])) / TICKS_PER_SEC - ) - - process_metrics.register_callback( - "virtual_memory_bytes", - lambda: int(stats["vsize"]) - ) - process_metrics.register_callback( - "resident_memory_bytes", - lambda: int(stats["rss"]) * BYTES_PER_PAGE - ) - - process_metrics.register_callback( - "start_time_seconds", - lambda: boot_time + int(stats["starttime"]) / TICKS_PER_SEC - ) - - if HAVE_PROC_SELF_FD: - process_metrics.register_callback( - "open_fds", - lambda: _count_fds() - ) - - if HAVE_PROC_SELF_LIMITS: - def _get_max_fds(): - with open("/proc/self/limits") as limits: - for line in limits: - if not line.startswith("Max open files "): - continue - # Line is Max open files $SOFT $HARD - return int(line.split()[3]) - return None - - process_metrics.register_callback( - "max_fds", - lambda: _get_max_fds() - ) |