#6727 "A metric that bursts now and then opens anomalies at hours whose usual
peak reads 0". usual_peak is the p90 of a slot's hourly max, so a metric that
bursts in under about 1 hour in 10 reads 0 there however often it bursts across
the day. #6723 "An anomaly opens on a burst of minutes inside the metric's usual
peak, so most rows aren't outside the norm" therefore still opened on those.
usual_anywhere is the median, across the hours of the day, of each hour's
highest peak. Height is now judged against the greater of it and the slot's
usual peak. Bursts at any hour lift the median; a job at a time of its own
raises a few hours and leaves it low, so the same level at another time of day
is still an anomaly, as System 182 rules. A held level still opens.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Rows on the live instance were mostly bursts of a few minutes: 28 of 52
peaked within the metric's own usual peak, and 42 of 52 latest occurrences
lasted 30 minutes or less, which is what a burst shorter than the 15-minute
average looks like once its span is back-dated. Nothing asked how high or how
long, as the System 182 ruling says a normal records.
A departure now also has to be past the slot's usual peak, or held: the
median of the last hour over the same line. Those spans were also keeping the
burstiest hours out of learning, lowering the usual lines further.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
CI 9128: the host vitals and monitor templates required the new grades, so
callers (and tests) that render them without one failed; they now fall back
to status_class. The new integration test read outside begin(), which
autobegan the session.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Host CPU, memory and load per core, container CPU and memory, and every
monitor's response time learn a normal per hour (milestone 513, System 182).
A reading past its fixed cutoff but within its normal reads healthy and says
what is usual at this hour; one well out of it keeps its grade and is a
metric anomaly. Disk, a monitor down and an agent offline keep their cutoffs.
- Each normal's floor, the smallest departure that counts, is a setting:
Settings -> Thresholds -> Normals (norms.floor.*). Defaults: host CPU 10
points, host memory 5, load per core 10, container CPU 10 points of one
core, container memory 5, monitor response 100 ms; Traefik's 2-point 4xx
and 50 ms p95 floors move there from constants. learn_normal takes a
floor function (floor_setting) read at each pass.
- learn_normal(parts=False): a host learns, its cores don't.
- Ingest records load_pct (load_1m / cores x 100), the figure pages grade.
- Shared grading: anomalies.against / graded, worst_reading(normals=),
hosts' host_grades, docker usage(thresholds=, norms=), monitors'
latency_grade. Applied to host vitals, the Hosts widget, MCP overview,
Docker usage, and the monitor list, widget and page.
- The monitor and container pages list their anomalies.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
#5741 "Traefik routers are graded against their own normal", milestone 513.
- A router's 4xx share and p95 learn their normal (learn_normal in the
plugin's setup). Once a router has 5 days of history, a reading over the
fixed cutoff but inside its normal is healthy, and the healthy table says
it is usual for that router. One out of its normal is a warning that says
what is usual, and a metric anomaly.
- The 5xx share is a failure: fixed cutoff always, whatever the history or
traffic (System 182's ruling).
- A 4xx share over fewer requests than Settings -> Thresholds' new "Fewest
requests to judge 4xx" (30 per 15 minutes) isn't graded on the page, and
isn't judged for anomalies.
- Core: learn_normal(gate=(metric, least)) judges a key only while its
resource's gate metric averages at least `least`; `least` may be a
function, so it follows a setting. learn_normal(since=...) learns only
from history after a moment: Traefik latency learns from #5755's
per-scrape figures only.
- The Traefik page lists the routers' metric anomalies of the last 30 days
(_anomaly_card.html). The dashboard widget keeps its why to problems.
- Thresholds and docs say when the cutoffs give way to a normal.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
The app's pooled connections belong to the loop that opened them, so a
second asyncio.run in one test failed with "attached to a different loop"
(run 9116). Tests that do several passes now await them in one coroutine.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
#5740 "A metric that departs from its normal is recorded as an anomaly to
review, and is findable after it ends", milestone 513.
- Every minute each learned key's last 15 minutes is judged against its
hour's normal: above the usual hold x1.25 and by the metric's floor opens
an occurrence, which ends when the level comes back.
- metric_anomalies holds one row per item to review; a repeat while it
still waits joins it as an occurrence (metric_anomaly_spans).
- An ended row nobody reviews within anomalies.review_days (14, Settings ->
Thresholds) lapses; an ongoing one never does.
- Learning skips every hour an occurrence covers unless its anomaly was
marked normal: no normal is learned without review.
- Alerts -> Anomalies lists those to review first, then the reviewed and
lapsed under day dividers; marking is operator/admin and audited.
- The Overview widget and get_overview warn of open ones and count those
to review; the host page shows its own; the weekly report lists the
week's and the lapsed; MCP list_anomalies and review_anomaly.
- Reviewed and lapsed rows are pruned at data.retention_days, and kept
in backups like alert history.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
bvandeusenandClaude Opus 5.5