diff options
| -rw-r--r-- | changelog.d/7536.misc | 1 | ||||
| -rw-r--r-- | synapse/metrics/__init__.py | 79 |
2 files changed, 79 insertions, 1 deletions
diff --git a/changelog.d/7536.misc b/changelog.d/7536.misc new file mode 100644 index 0000000000..c1211167fc --- /dev/null +++ b/changelog.d/7536.misc @@ -0,0 +1 @@ +Synapse now exports [detailed allocator statistics](https://doc.pypy.org/en/latest/gc_info.html#gc-get-stats) and basic GC timings as Prometheus metrics (`pypy_gc_time_seconds_total` and `pypy_memory_bytes`) when run under PyPy. Contributed by Ivan Shapovalov. diff --git a/synapse/metrics/__init__.py b/synapse/metrics/__init__.py index d2fd29acb4..9cf31f96b3 100644 --- a/synapse/metrics/__init__.py +++ b/synapse/metrics/__init__.py @@ -26,7 +26,12 @@ 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 @@ -338,6 +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 # |