bvandeusenandClaude Opus 5.5
4c84bc8560
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>
28 lines
1.1 KiB
Python
28 lines
1.1 KiB
Python
"""Each metric's normal, by time slot (#5739): the slot arithmetic and the
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registry. Learning itself runs in SQL; tests/integration/test_norms.py
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covers it against Postgres."""
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from __future__ import annotations
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from datetime import datetime, timedelta, timezone
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from steward.core import norms
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def test_a_day_slot_is_the_utc_hour():
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at = datetime(2026, 10, 14, 2, 30, tzinfo=timezone(timedelta(hours=-5))) # 07:30 UTC
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assert norms.slot_of(at, "day") == 7
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def test_a_week_slot_counts_hours_from_monday_utc():
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monday = datetime(2026, 10, 12, 0, 10, tzinfo=timezone.utc)
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assert norms.slot_of(monday, "week") == 0
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assert norms.slot_of(monday + timedelta(days=2, hours=2), "week") == 50 # Wed 02:10
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assert norms.slot_of(monday + timedelta(days=6, hours=23), "week") == 167
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def test_a_learned_metric_is_registered_once_with_its_floor():
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norms.learn_normal("test", "x_pct", 2)
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norms.learn_normal("test", "x_pct", 3)
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assert norms.LEARNED[("test", "x_pct")] == norms.Learned("test", "x_pct", 3.0)
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del norms.LEARNED[("test", "x_pct")]
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