diff options
Diffstat (limited to 'synapse/metrics/__init__.py')
| -rw-r--r-- | synapse/metrics/__init__.py | 97 |
1 files changed, 88 insertions, 9 deletions
diff --git a/synapse/metrics/__init__.py b/synapse/metrics/__init__.py index bec3b13397..9cf31f96b3 100644 --- a/synapse/metrics/__init__.py +++ b/synapse/metrics/__init__.py @@ -20,13 +20,18 @@ import os import platform import threading import time -from typing import Dict, Union +from typing import Callable, Dict, Iterable, Optional, Tuple, Union import six import attr from prometheus_client import Counter, Gauge, Histogram -from prometheus_client.core import REGISTRY, GaugeMetricFamily, HistogramMetricFamily +from prometheus_client.core import ( + REGISTRY, + CounterMetricFamily, + GaugeMetricFamily, + HistogramMetricFamily, +) from twisted.internet import reactor @@ -59,10 +64,12 @@ class RegistryProxy(object): @attr.s(hash=True) class LaterGauge(object): - name = attr.ib() - desc = attr.ib() - labels = attr.ib(hash=False) - caller = attr.ib() + name = attr.ib(type=str) + desc = attr.ib(type=str) + labels = attr.ib(hash=False, type=Optional[Iterable[str]]) + # 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 = attr.ib(type=Callable[[], Union[Dict[Tuple[str, ...], float], float]]) def collect(self): @@ -125,7 +132,7 @@ class InFlightGauge(object): ) # Counts number of in flight blocks for a given set of label values - self._registrations = {} + self._registrations = {} # type: Dict # Protects access to _registrations self._lock = threading.Lock() @@ -226,7 +233,7 @@ class BucketCollector(object): # Fetch the data -- this must be synchronous! data = self.data_collector() - buckets = {} + buckets = {} # type: Dict[float, int] res = [] for x in data.keys(): @@ -240,7 +247,7 @@ class BucketCollector(object): res.append(["+Inf", sum(data.values())]) metric = HistogramMetricFamily( - self.name, "", buckets=res, sum_value=sum([x * y for x, y in data.items()]) + self.name, "", buckets=res, sum_value=sum(x * y for x, y in data.items()) ) yield metric @@ -336,6 +343,78 @@ class GCCounts(object): if not running_on_pypy: REGISTRY.register(GCCounts()) + +# +# PyPy GC / memory metrics +# + + +class PyPyGCStats(object): + def collect(self): + + # @stats is a pretty-printer object with __str__() returning a nice table, + # plus some fields that contain data from that table. + # unfortunately, fields are pretty-printed themselves (i. e. '4.5MB'). + stats = gc.get_stats(memory_pressure=False) # type: ignore + # @s contains same fields as @stats, but as actual integers. + s = stats._s # type: ignore + + # also note that field naming is completely braindead + # and only vaguely correlates with the pretty-printed table. + # >>>> gc.get_stats(False) + # Total memory consumed: + # GC used: 8.7MB (peak: 39.0MB) # s.total_gc_memory, s.peak_memory + # in arenas: 3.0MB # s.total_arena_memory + # rawmalloced: 1.7MB # s.total_rawmalloced_memory + # nursery: 4.0MB # s.nursery_size + # raw assembler used: 31.0kB # s.jit_backend_used + # ----------------------------- + # Total: 8.8MB # stats.memory_used_sum + # + # Total memory allocated: + # GC allocated: 38.7MB (peak: 41.1MB) # s.total_allocated_memory, s.peak_allocated_memory + # in arenas: 30.9MB # s.peak_arena_memory + # rawmalloced: 4.1MB # s.peak_rawmalloced_memory + # nursery: 4.0MB # s.nursery_size + # raw assembler allocated: 1.0MB # s.jit_backend_allocated + # ----------------------------- + # Total: 39.7MB # stats.memory_allocated_sum + # + # Total time spent in GC: 0.073 # s.total_gc_time + + pypy_gc_time = CounterMetricFamily( + "pypy_gc_time_seconds_total", "Total time spent in PyPy GC", labels=[], + ) + pypy_gc_time.add_metric([], s.total_gc_time / 1000) + yield pypy_gc_time + + pypy_mem = GaugeMetricFamily( + "pypy_memory_bytes", + "Memory tracked by PyPy allocator", + labels=["state", "class", "kind"], + ) + # memory used by JIT assembler + pypy_mem.add_metric(["used", "", "jit"], s.jit_backend_used) + pypy_mem.add_metric(["allocated", "", "jit"], s.jit_backend_allocated) + # memory used by GCed objects + pypy_mem.add_metric(["used", "", "arenas"], s.total_arena_memory) + pypy_mem.add_metric(["allocated", "", "arenas"], s.peak_arena_memory) + pypy_mem.add_metric(["used", "", "rawmalloced"], s.total_rawmalloced_memory) + pypy_mem.add_metric(["allocated", "", "rawmalloced"], s.peak_rawmalloced_memory) + pypy_mem.add_metric(["used", "", "nursery"], s.nursery_size) + pypy_mem.add_metric(["allocated", "", "nursery"], s.nursery_size) + # totals + pypy_mem.add_metric(["used", "totals", "gc"], s.total_gc_memory) + pypy_mem.add_metric(["allocated", "totals", "gc"], s.total_allocated_memory) + pypy_mem.add_metric(["used", "totals", "gc_peak"], s.peak_memory) + pypy_mem.add_metric(["allocated", "totals", "gc_peak"], s.peak_allocated_memory) + yield pypy_mem + + +if running_on_pypy: + REGISTRY.register(PyPyGCStats()) + + # # Twisted reactor metrics # |