feat(docker): retention + hourly rollup for metrics/events with Settings windows

Bounds Docker time-series growth (the main scaling concern). New
docker_metrics_hourly table + docker_006 migration; a plugin retention module
(docker.run_retention capability) rolls raw docker_metrics older than the raw
window into hourly averages (idempotent upsert), deletes the rolled raw rows,
then prunes stale rollups + lifecycle events. Core cleanup.py drives it each
hourly run via the capability (no plugin-model import), reading the three
retention windows fresh from settings so changes apply without restart (rule 25).

Settings → "Thresholds & Retention" gains a Docker retention card (raw /
rolled-up / events windows, working defaults 7/90/30 days). Unit tests cover the
hour-aligned cutoff/bucketing helpers; integration test exercises the real
rollup-average + prune across both windows.

Milestone 77 task #941.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_016Jg27rgypiW2efULXJDtMC

plugins/docker/models.py

@@ -4,6 +4,7 @@ import uuid
 from datetime import datetime, timezone
 from sqlalchemy import (
     BigInteger, Boolean, DateTime, Float, ForeignKey, Index, Integer, String, Text,
+    UniqueConstraint,
 )
 from sqlalchemy.orm import Mapped, mapped_column
 from steward.models.base import Base
@@ -87,6 +88,39 @@ class DockerMetric(Base):
     )
 
 
+class DockerMetricHourly(Base):
+    """Hourly rollup of docker_metrics — avg cpu/mem per container per hour.
+
+    Raw per-sample rows (~2880/container/day at 30s) are pruned beyond a short
+    window; before deletion they're aggregated here so multi-day history stays
+    cheap to store and query. One row per (host, container, hour bucket); the
+    unique constraint lets retention upsert idempotently if it re-runs before the
+    raw rows are deleted. `bucket` is the hour-truncated sample time.
+    """
+    __tablename__ = "docker_metrics_hourly"
+
+    id: Mapped[str] = mapped_column(
+        String(36), primary_key=True, default=lambda: str(uuid.uuid4())
+    )
+    host_id: Mapped[str] = mapped_column(
+        String(36), ForeignKey("hosts.id", ondelete="CASCADE"), nullable=False
+    )
+    container_name: Mapped[str] = mapped_column(String(255), nullable=False)
+    bucket: Mapped[datetime] = mapped_column(DateTime(timezone=True), nullable=False)
+    cpu_pct: Mapped[float] = mapped_column(Float, nullable=False, default=0.0)
+    mem_pct: Mapped[float] = mapped_column(Float, nullable=False, default=0.0)
+    mem_usage_bytes: Mapped[int] = mapped_column(BigInteger, nullable=False, default=0)
+    sample_count: Mapped[int] = mapped_column(Integer, nullable=False, default=0)
+
+    __table_args__ = (
+        # One bucket per container per host — the conflict target for the
+        # idempotent rollup upsert; doubles as the history-query index.
+        UniqueConstraint("host_id", "container_name", "bucket",
+                         name="uq_docker_metrics_hourly_bucket"),
+        Index("ix_docker_metrics_hourly_bucket", "bucket"),
+    )
+
+
 class DockerEvent(Base):
     """Lifecycle events derived by diffing consecutive host snapshots.