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-rw-r--r--synapse/metrics/__init__.py79
1 files changed, 78 insertions, 1 deletions
diff --git a/synapse/metrics/__init__.py b/synapse/metrics/__init__.py
index d2fd29ac..9cf31f96 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
#