feat: alert engine stage 1 — rules, events, state machine, CRUD

Replaces the POC single-threshold check with a real per-rule engine over
the live monitor feed.

- AlertRule / AlertEvent tables (auto-created via create_all; no migration).
  Rule = {metric, comparison, threshold_db, duration_s, clear_margin_db,
  schedule, channels, recipients}.
- alerts.py: per-(unit,rule) state machine IDLE->ACTIVE->IDLE with duration
  debounce (both edges) + clear_margin hysteresis; onset/clear are distinct
  events; optional nighttime schedule; rule cache w/ invalidation. The
  state-machine core (_evaluate_step) is pure (no DB/clock) for testing.
- Dispatch is a server log (POC); _dispatch() is the seam for a Terra-View
  webhook (email/SMS) later.
- CRUD: POST/GET/PUT/DELETE /{unit}/alerts/rules, GET /{unit}/alerts/events,
  POST /{unit}/alerts/events/{id}/ack.
- test_alert_evaluator.py: synthetic level series proves onset debounce,
  spike rejection, hysteresis hold, and below-comparison (4/4 pass, no device).

Source-agnostic: the same rules transfer unchanged if a unit's feed is later
sourced from FTP intervals instead of the DOD monitor.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
This commit is contained in:
2026-06-09 01:04:03 +00:00
parent aa3e088b64
commit 9c43e68534
4 changed files with 444 additions and 48 deletions
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"""
Alert evaluation (POC).
Threshold alert engine.
Receives each monitor snapshot and fires an alert when a configured metric
exceeds a threshold, with a cooldown so a sustained loud period doesn't spam.
Each unit can have any number of AlertRules. A rule is evaluated against the
unit's live monitor snapshots via a small per-(unit, rule) state machine:
The RULE here is intentionally simple and swappable. Instantaneous Lp vs a
sustained window vs L10 is still an open design decision — this evaluator is the
single plug point for it. For the POC the rule is "instantaneous metric >
threshold, rate-limited by a cooldown", and dispatch is just a server-side log.
Wire email/SMS (likely via a Terra-View webhook) into _dispatch() later.
IDLE --(metric exceeds threshold for duration_s)--> ACTIVE (fire ONSET)
ACTIVE --(metric recovers past hysteresis for duration_s)--> IDLE (fire CLEAR)
Config via env:
- ALERT_ENABLED (default true)
- ALERT_METRIC which snapshot field to test: lp/leq/lmax/ln1/ln2 (default lp)
- ALERT_THRESHOLD_DB numeric dB threshold (default 85)
- ALERT_COOLDOWN_SECONDS min seconds between alerts per unit (default 60)
duration_s debounces both edges; clear_margin_db adds hysteresis so a level
hovering at the threshold doesn't flap. Onset and clear are distinct events.
The state-machine logic (`_evaluate_step`) is intentionally pure — no DB, no
real clock — so it can be unit-tested with a synthetic level series and a fake
clock. The AlertEvaluator wraps it with rule loading, scheduling, persistence,
and dispatch. Dispatch is a server log for now (POC); the seam to POST events to
a Terra-View webhook (email/SMS) is _dispatch().
"""
import asyncio
import logging
import os
from typing import Dict
from dataclasses import dataclass
from datetime import datetime, timedelta
from typing import Dict, List, Optional, Tuple
logger = logging.getLogger(__name__)
# Local timezone offset for schedule windows (same env var services.py uses).
_TZ_OFFSET_HOURS = float(os.getenv("TIMEZONE_OFFSET", "-5"))
# How long to cache a unit's rules before re-querying the DB (rules change rarely).
_RULE_CACHE_TTL_S = 15.0
@dataclass
class RuleState:
"""In-memory runtime state for one (unit, rule)."""
phase: str = "idle" # "idle" | "active"
edge_since: Optional[float] = None # when the current edge condition began (clock time)
peak: float = 0.0
event_id: Optional[int] = None # the open AlertEvent row (for the clear update)
def _exceeds(value: float, rule) -> bool:
if rule.comparison == "below":
return value < rule.threshold_db
return value > rule.threshold_db
def _recovered(value: float, rule) -> bool:
margin = rule.clear_margin_db or 0.0
if rule.comparison == "below":
return value > rule.threshold_db + margin
return value < rule.threshold_db - margin
def _evaluate_step(state: RuleState, value: float, now: float, rule) -> Optional[str]:
"""Advance the state machine by one reading.
Pure: mutates `state`, returns 'onset' | 'clear' | None. `now` is injected so
tests can drive a fake clock.
"""
duration = rule.duration_s or 0
if state.phase == "idle":
if _exceeds(value, rule):
if state.edge_since is None:
state.edge_since = now
if now - state.edge_since >= duration:
state.phase = "active"
state.edge_since = None
state.peak = value
return "onset"
else:
state.edge_since = None
return None
# active
if rule.comparison == "below":
state.peak = min(state.peak, value)
else:
state.peak = max(state.peak, value)
if _recovered(value, rule):
if state.edge_since is None:
state.edge_since = now
if now - state.edge_since >= duration:
state.phase = "idle"
state.edge_since = None
return "clear"
else:
state.edge_since = None
return None
def _in_window(now_minutes: int, start: str, end: str) -> bool:
"""Is now_minutes (minutes since local midnight) within [start, end)?
Handles wraparound windows like 22:0007:00."""
def _m(s: str) -> int:
h, m = s.split(":")
return int(h) * 60 + int(m)
s, e = _m(start), _m(end)
if s == e:
return True
if s < e:
return s <= now_minutes < e
return now_minutes >= s or now_minutes < e # wraparound
class AlertEvaluator:
def __init__(self):
self.enabled = os.getenv("ALERT_ENABLED", "true").lower() == "true"
self.metric = os.getenv("ALERT_METRIC", "lp").lower()
self.threshold_db = float(os.getenv("ALERT_THRESHOLD_DB", "85"))
self.cooldown_s = float(os.getenv("ALERT_COOLDOWN_SECONDS", "60"))
self._last_fired: Dict[str, float] = {}
logger.info(
f"[ALERT] evaluator ready: enabled={self.enabled} metric={self.metric} "
f"threshold={self.threshold_db}dB cooldown={self.cooldown_s}s"
)
self._states: Dict[Tuple[str, int], RuleState] = {}
self._rule_cache: Dict[str, Tuple[float, list]] = {} # unit_id -> (fetched_at, rules)
logger.info("[ALERT] rule-based evaluator ready")
async def evaluate(self, unit_id: str, snap) -> None:
"""Evaluate one snapshot; fire (log) if the metric exceeds threshold."""
if not self.enabled:
"""Evaluate every enabled rule for this unit against one snapshot."""
rules = self._get_rules(unit_id)
if not rules:
return
raw = getattr(snap, self.metric, None)
try:
level = float(raw)
except (TypeError, ValueError):
return # missing / non-numeric (e.g. "-.-")
if level <= self.threshold_db:
return
# Cooldown — use the event loop clock (Math.random/Date.now-free).
now = asyncio.get_running_loop().time()
if now - self._last_fired.get(unit_id, 0.0) < self.cooldown_s:
return
self._last_fired[unit_id] = now
for rule in rules:
if not self._in_schedule(rule):
continue
raw = getattr(snap, rule.metric, None)
try:
value = float(raw)
except (TypeError, ValueError):
continue # missing / non-numeric ("-.-")
state = self._states.setdefault((unit_id, rule.id), RuleState())
action = _evaluate_step(state, value, now, rule)
if action == "onset":
await self._on_onset(unit_id, rule, value, state)
elif action == "clear":
await self._on_clear(unit_id, rule, value, state)
await self._dispatch(unit_id, level)
# -- rule loading (cached) ----------------------------------------------
async def _dispatch(self, unit_id: str, level: float) -> None:
"""POC dispatch: server-side log. Swap in email/SMS here later."""
logger.warning(
f"[ALERT] {unit_id}: {self.metric.upper()}={level:.1f} dB exceeded "
f"threshold {self.threshold_db:.1f} dB"
def _get_rules(self, unit_id: str) -> list:
loop_now = asyncio.get_running_loop().time()
cached = self._rule_cache.get(unit_id)
if cached and loop_now - cached[0] < _RULE_CACHE_TTL_S:
return cached[1]
rules = self._load_rules(unit_id)
self._rule_cache[unit_id] = (loop_now, rules)
return rules
def _load_rules(self, unit_id: str) -> list:
from app.database import SessionLocal
from app.models import AlertRule
db = SessionLocal()
try:
return db.query(AlertRule).filter_by(unit_id=unit_id, enabled=True).all()
except Exception as e:
logger.warning(f"[ALERT] failed to load rules for {unit_id}: {e}")
return []
finally:
db.close()
def invalidate(self, unit_id: Optional[str] = None) -> None:
"""Drop cached rules so a change is picked up immediately."""
if unit_id is None:
self._rule_cache.clear()
else:
self._rule_cache.pop(unit_id, None)
# -- scheduling ----------------------------------------------------------
def _in_schedule(self, rule) -> bool:
if not rule.schedule_start or not rule.schedule_end:
day_ok = self._day_ok(rule)
return day_ok
local = datetime.utcnow() + timedelta(hours=_TZ_OFFSET_HOURS)
if not self._day_ok(rule, local):
return False
return _in_window(local.hour * 60 + local.minute, rule.schedule_start, rule.schedule_end)
@staticmethod
def _day_ok(rule, local: Optional[datetime] = None) -> bool:
if not rule.schedule_days:
return True
if local is None:
local = datetime.utcnow() + timedelta(hours=_TZ_OFFSET_HOURS)
allowed = {int(d) for d in str(rule.schedule_days).split(",") if d.strip() != ""}
return local.weekday() in allowed # Mon=0
# -- event persistence + dispatch ---------------------------------------
async def _on_onset(self, unit_id: str, rule, value: float, state: RuleState) -> None:
from app.database import SessionLocal
from app.models import AlertEvent
db = SessionLocal()
try:
evt = AlertEvent(
rule_id=rule.id, unit_id=unit_id, rule_name=rule.name,
metric=rule.metric, threshold_db=rule.threshold_db,
onset_value=value, peak_value=value, status="active",
)
db.add(evt)
db.commit()
db.refresh(evt)
state.event_id = evt.id
except Exception as e:
logger.warning(f"[ALERT] failed to record onset for {unit_id}: {e}")
finally:
db.close()
await self._dispatch(
"ONSET", unit_id, rule,
f"{rule.metric.upper()}={value:.1f} dB "
f"{'<' if rule.comparison == 'below' else '>'} {rule.threshold_db:.1f} dB"
f"{f' for {rule.duration_s}s' if rule.duration_s else ''}",
)
async def _on_clear(self, unit_id: str, rule, value: float, state: RuleState) -> None:
peak = state.peak
from app.database import SessionLocal
from app.models import AlertEvent
db = SessionLocal()
try:
if state.event_id is not None:
evt = db.query(AlertEvent).filter_by(id=state.event_id).first()
if evt:
evt.clear_at = datetime.utcnow()
evt.peak_value = peak
evt.status = "cleared"
db.commit()
except Exception as e:
logger.warning(f"[ALERT] failed to record clear for {unit_id}: {e}")
finally:
db.close()
state.event_id = None
await self._dispatch(
"CLEAR", unit_id, rule,
f"recovered to {value:.1f} dB (peak {peak:.1f} dB)",
)
# Module-level singleton
async def _dispatch(self, kind: str, unit_id: str, rule, detail: str) -> None:
"""POC dispatch: server log. Swap in a Terra-View webhook (email/SMS) here."""
logger.warning(f"[ALERT:{kind}] {unit_id} '{rule.name}': {detail}")
# Module-level singleton (the monitor calls alert_evaluator.evaluate per snapshot)
alert_evaluator = AlertEvaluator()