feat(norms): Steward learns each metric's normal per hour of day, then week (#5739)

A metric registered with learn_normal() gets, for every resource reporting
it, a usual hold (the 90th percentile across past days of each hour's p95)
and a usual peak for each slot:
- an hour of the day once 5 days of history exist;
- an hour of the week once history reaches back 3 weeks, so weekly jobs are
  learned too.
Each slot takes in the hours either side, so a job that runs a little late
stays normal. One SQL statement relearns everything hourly into
metric_norms, from the rollup plus the raw window not rolled up yet;
norms_at() reads the slot a moment falls in. Nothing is registered yet:
Traefik (#5741) and hosts (#5742) opt in.

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

steward/migrations/versions/0045_metric_norms.py

@@ -0,0 +1,33 @@
+"""What each learned metric usually does in each time slot (#5739).
+
+Revision ID: 0045_metric_norms
+Revises: 0044_hourly_p95
+Create Date: 2026-10-14
+"""
+from typing import Sequence, Union
+from alembic import op
+import sqlalchemy as sa
+
+revision: str = "0045_metric_norms"
+down_revision: Union[str, None] = "0044_hourly_p95"
+branch_labels: Union[str, Sequence[str], None] = None
+depends_on: Union[str, Sequence[str], None] = None
+
+
+def upgrade() -> None:
+    op.create_table(
+        "metric_norms",
+        sa.Column("source_module", sa.String(64), primary_key=True),
+        sa.Column("resource_name", sa.String(255), primary_key=True),
+        sa.Column("metric_name", sa.String(128), primary_key=True),
+        sa.Column("slot", sa.SmallInteger, primary_key=True),
+        sa.Column("kind", sa.String(8), nullable=False),
+        sa.Column("usual_hold", sa.Float, nullable=False),
+        sa.Column("usual_peak", sa.Float, nullable=False),
+        sa.Column("days_seen", sa.Integer, nullable=False),
+        sa.Column("updated_at", sa.DateTime(timezone=True), nullable=False),
+    )
+
+
+def downgrade() -> None:
+    op.drop_table("metric_norms")