bvandeusenandClaude Opus 5.5
f3433fe3ce
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>
65 lines
2.6 KiB
Python
65 lines
2.6 KiB
Python
# plugins/traefik/__init__.py
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from __future__ import annotations
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from typing import TYPE_CHECKING
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if TYPE_CHECKING:
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from quart import Quart
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_app: "Quart | None" = None
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def setup(app: "Quart") -> None:
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global _app
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_app = app
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from .models import ( # noqa: F401
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TraefikAccessSummary, TraefikCert, TraefikGlobalStat, TraefikMetric, TraefikStatusCode,
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)
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from steward.core.cleanup import prune_by_age
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# Samples older than data.retention_days are pruned by the cleanup (#5155).
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prune_by_age(TraefikMetric.scraped_at)
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prune_by_age(TraefikStatusCode.scraped_at)
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prune_by_age(TraefikGlobalStat.scraped_at)
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prune_by_age(TraefikAccessSummary.period_end)
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# Each router's 4xx share and p95 learn their normal (#5741), judged only
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# while the router answers the Thresholds minimum of requests a window
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# (read at each pass, so a saved change applies at once). Latency is
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# learned from the scrape-by-scrape figures only: before #5755 it was a
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# percentile of every response since Traefik started.
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from datetime import datetime, timezone
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from steward.core.norms import floor_setting, learn_normal
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from .routes import STATE_WINDOW, min_requests
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gate = ("request_rate",
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lambda: min_requests(app.config.get("THRESHOLDS", {})) / STATE_WINDOW.total_seconds())
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learn_normal("traefik", "error_rate_4xx_pct", floor_setting(app, "router_4xx_pct"), gate=gate)
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learn_normal("traefik", "latency_p95_ms", floor_setting(app, "router_p95_ms"), gate=gate,
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since=datetime(2026, 10, 14, 18, 47, tzinfo=timezone.utc))
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def get_scheduled_tasks() -> list:
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from .scheduler import make_scrape_task, make_access_log_task
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tasks = [make_scrape_task(_app)]
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access_log_cfg = _app.config["PLUGINS"]["traefik"].get("access_log", {})
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if not isinstance(access_log_cfg, dict):
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access_log_cfg = {}
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if access_log_cfg.get("enabled", False):
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tasks.append(make_access_log_task(_app))
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return tasks
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def get_blueprint():
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from .routes import traefik_bp
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return traefik_bp
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def get_nav() -> list[dict]:
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# Surfaces in the sidebar's Infrastructure group (Traefik services view).
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return [{"label": "Traefik", "href": "/plugins/traefik/"}]
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def get_alert_metrics() -> dict[str, list[str]]:
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"""What scheduler.py records for alert rules: per router (resource = the
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router name) and cert_expiry_days per certificate (resource = its CN)."""
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return {"traefik": ["request_rate", "error_rate_4xx_pct", "error_rate_5xx_pct",
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"latency_p50_ms", "latency_p95_ms", "latency_p99_ms",
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"response_bytes_rate", "cert_expiry_days"]}
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