feat(metrics): each rolled-up hour keeps the level it held, its p95 (#5738)

plugin_metrics_hourly gains value_p95 beside value_avg and value_max. A
two-minute backup spike raises the hour's peak and leaves its p95 low; an
hour spent at that level raises both. Learned normals (milestone 513) need
that difference to call a recurring spike usual without calling the same
level held at another hour usual too. Hours rolled up before this keep a
NULL p95 and read as their average.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>

docs/architecture.md

@@ -87,6 +87,22 @@ Core tasks registered in `app._task_registry`:
 
 ---
 
+## Metric Store
+
+Every plugin and monitor records into one store keyed by (source, resource, metric):
+- `plugin_metrics` holds raw samples for `metrics.retention.raw_days` (7 by default).
+- `plugin_metric_latest` holds each key's newest value.
+- `data_cleanup` rolls raw samples older than the raw window into `plugin_metrics_hourly`, kept for `metrics.retention.rollup_days` (90 by default).
+
+Each rolled-up hour keeps three figures:
+- `value_avg`: the hour's average.
+- `value_max`: its peak.
+- `value_p95`: the level it held for all but its briefest 5%, about 3 minutes.
+
+A two-minute spike raises the peak and leaves the p95 low; an hour spent at that level raises both. Learned normals use this to tell a recurring spike from a held level. Hours rolled up before the p95 was kept have it NULL; read those as their average.
+
+---
+
 ## Database Session Pattern
 
 `app.db_sessionmaker` is an SQLAlchemy `async_sessionmaker`. All DB access follows this pattern: