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ChuckBuildsandClaude Opus 5 dab4b3ea57 fix: use a monotonic clock and only mark metrics persisted once written
Two review findings on the throttle, both right.

The interval compared wall-clock timestamps. These devices have no RTC, so
the clock jumps by however far off boot-time was the moment NTP first syncs
-- a forward jump would allow an early write, a backward one would stall the
snapshot well past the interval. time.monotonic() is not subject to either.

The timestamp was also recorded before cache_manager.set(). A set() that
raised would buy the next interval's silence without leaving a snapshot
behind, which is the one case where skipping the write is least affordable.
Recorded after the write lands instead, so a failure is retried on the next
call.

Verified by restoring the original ordering: the new test then reports one
write where two are expected.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01STMbQE4YctTacQXfbYqKuW
2026-08-20 07:42:24 -04:00
ChuckBuildsandClaude Opus 5 0fd2bfae99 perf(plugins): stop rewriting a plugin's metrics file on every call
Plugin metrics were persisted to the cache inside monitor_call, so every
call by every plugin rewrote a small JSON file. Measured on a running rig:
one plugin's plugin_metrics file changed nine times a minute, with fourteen
such files active. Each is around 350 bytes, which on ext4 costs a 4KB block
plus a journal entry, so the cost is dominated by the write itself rather
than the payload. Cache writes accounted for essentially all of that device's
2.4 MB/min of SD traffic, on a card that wears out and has already failed
twice on the other rig.

Metrics cannot be de-duplicated the way health state can, because call_count
changes on every call and the timings usually do too. So they are rate-limited
instead: at most one write per plugin per 30 seconds.

The in-memory copy stays authoritative and exact -- a plugin's call_count is
still precise the instant after it runs. Only the cross-process snapshot the
web UI reads is delayed, and telemetry up to half a minute old is still a fair
description of a long-running plugin.

reset_metrics clears the throttle timestamp, so a reset is not left showing a
deleted key for the rest of the interval.

Extrapolating the sampled rate, this takes metric writes from roughly 126 a
minute to 28. Health persistence, the other half of the churn, is handled
separately in #475.

Verified by reverting the throttle: the churn test then reports 50 writes for
50 calls. 88 tests pass across resource monitor, plugin system and web API.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01STMbQE4YctTacQXfbYqKuW
2026-08-20 07:06:21 -04:00
4 changed files with 118 additions and 119 deletions
+54 -12
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@@ -49,6 +49,20 @@ class ResourceMetrics:
self.total_execution_time = self.total_execution_time / self.call_count self.total_execution_time = self.total_execution_time / self.call_count
#: How often a plugin's metrics are written to the cache, in seconds.
#:
#: Persisting on every call meant a small file rewritten roughly nine times a
#: minute per plugin. On a rig with fourteen active plugins that was ~126
#: writes a minute for metrics alone, and since each ~350-byte file costs a
#: 4KB block plus an ext4 journal entry, it dominated the device's write
#: volume -- on an SD card, which wears out.
#:
#: The in-memory copy stays authoritative and exact; only the cross-process
#: snapshot the web UI reads is delayed, and telemetry up to half a minute old
#: is still a fair description of a long-running plugin.
_METRICS_PERSIST_INTERVAL = 30.0
class PluginResourceMonitor: class PluginResourceMonitor:
""" """
Monitors resource usage for plugins. Monitors resource usage for plugins.
@@ -75,6 +89,10 @@ class PluginResourceMonitor:
# Resource metrics per plugin # Resource metrics per plugin
self._metrics: Dict[str, ResourceMetrics] = {} self._metrics: Dict[str, ResourceMetrics] = {}
self._limits: Dict[str, ResourceLimits] = {} self._limits: Dict[str, ResourceLimits] = {}
# When each plugin's metrics last reached the cache. Metrics change on
# every call, so they cannot be de-duplicated the way health state can;
# they are rate-limited instead. See _METRICS_PERSIST_INTERVAL.
self._metrics_persisted_at: Dict[str, float] = {}
# Thread-local storage for execution tracking # Thread-local storage for execution tracking
self._local = threading.local() self._local = threading.local()
@@ -232,18 +250,8 @@ class PluginResourceMonitor:
# CPU is harder to measure per-call, so we track it separately # CPU is harder to measure per-call, so we track it separately
metrics.cpu_percent = self._get_process_cpu_percent() metrics.cpu_percent = self._get_process_cpu_percent()
# Persist metrics # Persist metrics, at most once per interval per plugin.
cache_key = self._get_metrics_key(plugin_id) self._persist_metrics(plugin_id, metrics)
self.cache_manager.set(cache_key, {
'memory_mb': metrics.memory_mb,
'cpu_percent': metrics.cpu_percent,
'execution_time': metrics.execution_time,
'call_count': metrics.call_count,
'total_execution_time': metrics.total_execution_time,
'max_execution_time': metrics.max_execution_time,
'min_execution_time': metrics.min_execution_time if metrics.min_execution_time != float('inf') else 0.0,
'last_update_time': metrics.last_update_time
})
# Check limits # Check limits
if limits: if limits:
@@ -363,6 +371,37 @@ class PluginResourceMonitor:
summaries[plugin_id] = self.get_metrics_summary(plugin_id) summaries[plugin_id] = self.get_metrics_summary(plugin_id)
return summaries return summaries
def _persist_metrics(self, plugin_id: str, metrics: ResourceMetrics,
force: bool = False) -> None:
"""Write a plugin's metrics to the cache, at most once per interval.
Caller must hold ``self._lock``.
"""
# Monotonic, not wall clock: these devices have no RTC, so the clock
# jumps by however far off boot-time was the moment NTP first syncs.
# A forward jump would allow an early write, a backward one would
# stall the snapshot well past the interval.
now = time.monotonic()
if not force and now - self._metrics_persisted_at.get(plugin_id, 0.0) \
< _METRICS_PERSIST_INTERVAL:
return
cache_key = self._get_metrics_key(plugin_id)
self.cache_manager.set(cache_key, {
'memory_mb': metrics.memory_mb,
'cpu_percent': metrics.cpu_percent,
'execution_time': metrics.execution_time,
'call_count': metrics.call_count,
'total_execution_time': metrics.total_execution_time,
'max_execution_time': metrics.max_execution_time,
'min_execution_time': (metrics.min_execution_time
if metrics.min_execution_time != float('inf')
else 0.0),
'last_update_time': metrics.last_update_time,
})
# Only after the write lands. Marking it first would mean a failed
# set() bought the next interval's silence without leaving a snapshot.
self._metrics_persisted_at[plugin_id] = now
def reset_metrics(self, plugin_id: str) -> None: def reset_metrics(self, plugin_id: str) -> None:
"""Reset metrics for a plugin.""" """Reset metrics for a plugin."""
with self._lock: with self._lock:
@@ -370,4 +409,7 @@ class PluginResourceMonitor:
self._metrics[plugin_id] = ResourceMetrics() self._metrics[plugin_id] = ResourceMetrics()
cache_key = self._get_metrics_key(plugin_id) cache_key = self._get_metrics_key(plugin_id)
self.cache_manager.delete(cache_key) self.cache_manager.delete(cache_key)
# Let the next call persist immediately rather than leaving the
# deleted key absent for the rest of the interval.
self._metrics_persisted_at.pop(plugin_id, None)
-12
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@@ -8,18 +8,6 @@ Type=simple
User=root User=root
WorkingDirectory=__PROJECT_ROOT_DIR__ WorkingDirectory=__PROJECT_ROOT_DIR__
Environment=PYTHONDONTWRITEBYTECODE=1 Environment=PYTHONDONTWRITEBYTECODE=1
# glibc gives each allocating thread its own malloc arena, up to 8 x CPU count,
# and an arena that has grown is never handed back to the OS. This process runs
# 9 threads on a 3-core Pi, so the ceiling is 24 arenas -- and a rig measured at
# 1030 MB resident held 23 large anonymous mappings on 64 MB-aligned addresses,
# 920 MB of them, while the live data it was actually holding (widest scroll
# strip seen: 35,746 x 64) accounts for roughly 15 MB. That gap is arena bloat,
# not leaked objects: RSS was flat across repeated sampling, not climbing.
#
# Capping the arenas trades a little allocator concurrency for a large amount of
# resident memory on a device that has neither to spare. 2 is the usual value;
# raise it if frame times regress.
Environment=MALLOC_ARENA_MAX=2
ExecStart=/usr/bin/python3 __PROJECT_ROOT_DIR__/run.py ExecStart=/usr/bin/python3 __PROJECT_ROOT_DIR__/run.py
# Restart=always, not on-failure: run.py exiting 0 (a clean shutdown path taken # Restart=always, not on-failure: run.py exiting 0 (a clean shutdown path taken
# for a reason that no longer applies, e.g. a config reload) would otherwise leave # for a reason that no longer applies, e.g. a config reload) would otherwise leave
+64
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@@ -127,3 +127,67 @@ class TestForceReload:
fresh = mon.get_metrics_summary("p", force_reload=True) fresh = mon.get_metrics_summary("p", force_reload=True)
assert fresh["call_count"] == 7 assert fresh["call_count"] == 7
assert any(c.kwargs.get("memory_ttl") == 0 for c in cache.get.call_args_list) assert any(c.kwargs.get("memory_ttl") == 0 for c in cache.get.call_args_list)
class TestMetricsPersistenceChurn:
"""Metrics are telemetry; writing them on every call wore the SD card.
Each write is a ~350-byte file, which on ext4 costs a 4KB block plus a
journal entry. At roughly nine calls a minute per plugin across fourteen
plugins it dominated the device's write volume.
"""
def test_repeated_calls_persist_once_per_interval(self):
cache = _cache()
mon = PluginResourceMonitor(cache, enable_monitoring=False)
for _ in range(50):
mon.monitor_call("p", lambda: None)
writes = [c for c in cache.set.call_args_list
if c.args and str(c.args[0]).startswith("plugin_metrics:")]
assert len(writes) == 1, (
f"50 calls produced {len(writes)} metric writes; expected 1")
def test_the_interval_elapsing_allows_the_next_write(self, monkeypatch):
import src.plugin_system.resource_monitor as rm
cache = _cache()
mon = PluginResourceMonitor(cache, enable_monitoring=False)
mon.monitor_call("p", lambda: None)
# pretend the interval has passed
mon._metrics_persisted_at["p"] -= rm._METRICS_PERSIST_INTERVAL + 1
mon.monitor_call("p", lambda: None)
writes = [c for c in cache.set.call_args_list
if c.args and str(c.args[0]).startswith("plugin_metrics:")]
assert len(writes) == 2
def test_in_memory_metrics_stay_exact_while_writes_are_skipped(self):
mon = PluginResourceMonitor(_cache(), enable_monitoring=False)
for _ in range(20):
mon.monitor_call("p", lambda: None)
assert mon.get_metrics("p").call_count == 20
def test_reset_lets_the_next_call_persist_immediately(self):
cache = _cache()
mon = PluginResourceMonitor(cache, enable_monitoring=False)
mon.monitor_call("p", lambda: None)
mon.reset_metrics("p")
mon.monitor_call("p", lambda: None)
writes = [c for c in cache.set.call_args_list
if c.args and str(c.args[0]).startswith("plugin_metrics:")]
assert len(writes) == 2, "reset should clear the throttle timestamp"
def test_a_failed_write_does_not_buy_the_next_interval_of_silence(self):
"""A set() that raises must not count as having persisted.
Marking the timestamp before the write would leave no snapshot in the
cache and still suppress the next 30 seconds of attempts.
"""
cache = _cache()
cache.set.side_effect = [OSError("disk full"), None]
mon = PluginResourceMonitor(cache, enable_monitoring=False)
with pytest.raises(OSError):
mon.monitor_call("p", lambda: None)
# the very next call must try again rather than skip the interval
mon.monitor_call("p", lambda: None)
writes = [c for c in cache.set.call_args_list
if c.args and str(c.args[0]).startswith("plugin_metrics:")]
assert len(writes) == 2, "a failed write should be retried, not skipped"
-95
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@@ -1,95 +0,0 @@
"""The display unit must cap glibc's malloc arenas.
glibc hands each allocating thread its own malloc arena, up to 8 x CPU count,
and an arena that has grown is never returned to the OS. This process runs
threads for the render loop, the update workers and the background fetchers, so
on a 3-core Pi the ceiling is 24 arenas.
Measured on a live rig, 2.5 hours in:
RSS 1030 MB
Private_Dirty 988 MB
anonymous mappings > 10 MB 23 (ceiling is 8 x 3 = 24)
largest few 104, 79, 66, 63, 63 MB, on 64 MB-aligned addresses
against live data that accounts for perhaps 15 MB -- the widest scroll strip
observed was 35,746 x 64, about 7 MB as RGB and the same again for its numpy
mirror. Repeated sampling showed RSS flat between 990 and 1030 MB rather than
climbing, so this is arena bloat rather than a leak: memory Python has freed
but glibc is holding per-arena.
The device had 59 MB free at the time.
Capping the arena count trades a little allocator concurrency for that resident
memory. The render loop is latency-sensitive, so if p99 frame time regresses the
right response is to raise this rather than remove it.
"""
import re
from pathlib import Path
import pytest
UNIT = (Path(__file__).resolve().parent.parent / "systemd" / "ledmatrix.service")
#: The value the unit is expected to carry. 2 is the usual choice for a
#: threaded Python process; 1-4 all keep some of the saving, but only one of
#: them is what this project ships.
EXPECTED_ARENA_MAX = 2
def _environment(unit_text):
return dict(
line.split("=", 2)[1:3] if line.count("=") >= 2 else (line.split("=", 1)[1], "")
for line in unit_text.splitlines()
if line.startswith("Environment=")
)
def test_the_unit_exists():
assert UNIT.is_file(), f"{UNIT} is missing"
def test_malloc_arena_max_is_capped():
env = _environment(UNIT.read_text(encoding="utf-8"))
assert "MALLOC_ARENA_MAX" in env, (
"the display unit does not cap glibc arenas; on a 3-core Pi the default "
"ceiling is 24 and a measured rig held 23 of them, 920 MB"
)
value = int(env["MALLOC_ARENA_MAX"])
# Pinned, not a range. A range let a change to 4 -- which hands most of the
# saving back -- pass unnoticed, which was the point of the finding that
# prompted this. Raising it is a legitimate response to a frame-time
# regression, but it should be a visible edit here rather than a silent
# drift, so the number lives in one place and changing it shows up in
# review.
assert value == EXPECTED_ARENA_MAX, (
f"MALLOC_ARENA_MAX={value}, expected {EXPECTED_ARENA_MAX}. If this was "
"raised deliberately because frame times regressed, update "
"EXPECTED_ARENA_MAX here and say so in the commit."
)
def test_the_reason_is_recorded_next_to_it():
"""A bare tuning knob invites removal by whoever meets it next."""
text = UNIT.read_text(encoding="utf-8")
index = text.index("Environment=MALLOC_ARENA_MAX")
preamble = text[:index].splitlines()[-12:]
comment = "\n".join(line for line in preamble if line.startswith("#"))
assert "arena" in comment.lower(), "no explanation precedes the setting"
assert re.search(r"\d", comment), (
"the explanation cites no measurement, so a reader cannot tell whether "
"it still applies to their hardware"
)
@pytest.mark.parametrize("unit", ["ledmatrix.service"])
def test_the_unit_still_parses_as_ini(unit):
"""systemd will refuse a malformed unit, and the panel stays dark."""
import configparser
path = UNIT.parent / unit
parser = configparser.ConfigParser(strict=False)
# systemd allows repeated keys; ConfigParser needs them merged, not rejected.
parser.read_string(path.read_text(encoding="utf-8"))
assert parser.has_section("Service")
assert parser.has_option("Service", "ExecStart")