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()
- )
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