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Introduced new parameters to fine-tune rollback ratio alerts and reduce false positives on low-traffic databases. Adjusted evaluation logic to account for minimum rollback counts and transaction volumes, ensuring more reliable alert thresholds. Updated .env.example and descriptions for better configuration clarity.
510 lines
20 KiB
Python
510 lines
20 KiB
Python
from __future__ import annotations
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from dataclasses import dataclass
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from datetime import datetime, timedelta, timezone
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import re
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import time
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import asyncpg
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from fastapi import HTTPException
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from sqlalchemy import desc, func, select
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from sqlalchemy.ext.asyncio import AsyncSession
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from app.core.config import get_settings
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from app.models.models import AlertDefinition, Metric, QueryStat, Target
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from app.schemas.alert import AlertStatusItem, AlertStatusResponse
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from app.services.collector import build_target_dsn
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settings = get_settings()
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_ALLOWED_COMPARISONS = {"gte", "gt", "lte", "lt"}
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_FORBIDDEN_SQL_WORDS = re.compile(
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r"\b(insert|update|delete|alter|drop|truncate|create|grant|revoke|vacuum|analyze|copy|call|do)\b",
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re.IGNORECASE,
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)
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_STATUS_CACHE_TTL_SECONDS = 15
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_status_cache: dict = {"expires": 0.0, "data": None}
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@dataclass
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class _RuleInput:
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key: str
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name: str
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description: str
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category: str
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value: float | None
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warning_threshold: float | None
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alert_threshold: float | None
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comparison: str = "gte"
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def invalidate_alert_cache() -> None:
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_status_cache["expires"] = 0.0
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_status_cache["data"] = None
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def validate_alert_thresholds(comparison: str, warning_threshold: float | None, alert_threshold: float) -> None:
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if comparison not in _ALLOWED_COMPARISONS:
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raise HTTPException(status_code=400, detail=f"Invalid comparison. Use one of {sorted(_ALLOWED_COMPARISONS)}")
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if warning_threshold is None:
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return
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if comparison in {"gte", "gt"} and warning_threshold > alert_threshold:
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raise HTTPException(status_code=400, detail="For gte/gt, warning_threshold must be <= alert_threshold")
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if comparison in {"lte", "lt"} and warning_threshold < alert_threshold:
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raise HTTPException(status_code=400, detail="For lte/lt, warning_threshold must be >= alert_threshold")
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def validate_alert_sql(sql_text: str) -> str:
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sql = sql_text.strip().rstrip(";")
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lowered = sql.lower().strip()
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if not lowered.startswith("select"):
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raise HTTPException(status_code=400, detail="Alert SQL must start with SELECT")
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if _FORBIDDEN_SQL_WORDS.search(lowered):
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raise HTTPException(status_code=400, detail="Only read-only SELECT statements are allowed")
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if ";" in sql:
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raise HTTPException(status_code=400, detail="Only a single SQL statement is allowed")
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return sql
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async def _connect_target(target: Target, timeout_seconds: int = 5) -> asyncpg.Connection:
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return await asyncpg.connect(dsn=build_target_dsn(target), timeout=timeout_seconds)
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async def run_scalar_sql_for_target(target: Target, sql_text: str) -> float:
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sql = validate_alert_sql(sql_text)
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conn: asyncpg.Connection | None = None
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try:
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conn = await _connect_target(target, timeout_seconds=6)
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row = await conn.fetchrow(sql)
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if not row:
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raise ValueError("Query returned no rows")
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value = row[0]
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return float(value)
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finally:
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if conn:
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await conn.close()
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def _compare(value: float, threshold: float, comparison: str) -> bool:
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if comparison == "gte":
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return value >= threshold
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if comparison == "gt":
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return value > threshold
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if comparison == "lte":
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return value <= threshold
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if comparison == "lt":
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return value < threshold
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return False
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def _severity_from_thresholds(
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value: float | None, comparison: str, warning_threshold: float | None, alert_threshold: float | None
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) -> str:
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if value is None or alert_threshold is None:
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return "unknown"
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if _compare(value, alert_threshold, comparison):
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return "alert"
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if warning_threshold is not None and _compare(value, warning_threshold, comparison):
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return "warning"
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return "ok"
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def _status_message(value: float | None, comparison: str, warning_threshold: float | None, alert_threshold: float | None) -> str:
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if value is None:
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return "No numeric value available"
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if alert_threshold is None:
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return f"Current value: {value:.2f}"
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if warning_threshold is None:
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return f"Current value: {value:.2f} (alert when value {comparison} {alert_threshold:.2f})"
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return (
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f"Current value: {value:.2f} "
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f"(warning when value {comparison} {warning_threshold:.2f}, alert when value {comparison} {alert_threshold:.2f})"
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)
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async def _latest_metric_value(db: AsyncSession, target_id: int, metric_name: str) -> float | None:
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row = await db.scalar(
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select(Metric.value)
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.where(Metric.target_id == target_id, Metric.metric_name == metric_name)
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.order_by(desc(Metric.ts))
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.limit(1)
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)
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return float(row) if row is not None else None
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async def _metric_delta(db: AsyncSession, target_id: int, metric_name: str, minutes: int) -> float | None:
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cutoff = datetime.now(timezone.utc) - timedelta(minutes=minutes)
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latest = await db.scalar(
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select(Metric.value)
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.where(Metric.target_id == target_id, Metric.metric_name == metric_name)
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.order_by(desc(Metric.ts))
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.limit(1)
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)
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oldest = await db.scalar(
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select(Metric.value)
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.where(Metric.target_id == target_id, Metric.metric_name == metric_name, Metric.ts >= cutoff)
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.order_by(Metric.ts.asc())
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.limit(1)
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)
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if latest is None or oldest is None:
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return None
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return max(0.0, float(latest) - float(oldest))
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async def _rollback_ratio_recent(
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db: AsyncSession, target_id: int, minutes: int, min_total_transactions: int, min_rollbacks: int
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) -> tuple[float | None, float, float]:
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commit_delta = await _metric_delta(db, target_id, "xact_commit", minutes=minutes)
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rollback_delta = await _metric_delta(db, target_id, "xact_rollback", minutes=minutes)
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if commit_delta is None or rollback_delta is None:
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return None, 0.0, 0.0
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tx_total = commit_delta + rollback_delta
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if tx_total < float(min_total_transactions):
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# Too little traffic in window, ratio would be noisy and misleading.
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return None, tx_total, rollback_delta
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if rollback_delta < float(min_rollbacks):
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# Ignore tiny rollback counts even if ratio appears high on low absolute numbers.
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return None, tx_total, rollback_delta
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return (rollback_delta / tx_total) if tx_total > 0 else None, tx_total, rollback_delta
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async def _latest_query_snapshot_max(db: AsyncSession, target_id: int, column_name: str) -> float | None:
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latest_ts = await db.scalar(select(func.max(QueryStat.ts)).where(QueryStat.target_id == target_id))
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if latest_ts is None:
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return None
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column = QueryStat.mean_time if column_name == "mean_time" else QueryStat.total_time
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value = await db.scalar(
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select(func.max(column)).where(QueryStat.target_id == target_id, QueryStat.ts == latest_ts)
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)
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return float(value) if value is not None else None
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async def _build_standard_rules(db: AsyncSession, target: Target) -> tuple[list[_RuleInput], list[AlertStatusItem]]:
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rules: list[_RuleInput] = []
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forced_items: list[AlertStatusItem] = []
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checked_at = datetime.now(timezone.utc)
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# 1) Connectivity with RTT threshold.
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start = time.perf_counter()
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conn: asyncpg.Connection | None = None
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try:
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conn = await _connect_target(target, timeout_seconds=4)
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await conn.fetchval("SELECT 1")
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connect_ms = (time.perf_counter() - start) * 1000
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rules.append(
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_RuleInput(
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key="connectivity_rtt_ms",
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name="Connectivity Latency",
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description="Checks whether the target is reachable and how long the connection handshake takes.",
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category="availability",
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value=connect_ms,
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warning_threshold=1000,
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alert_threshold=2500,
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comparison="gte",
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)
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)
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except Exception as exc:
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forced_items.append(
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AlertStatusItem(
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alert_key=f"std-connectivity-down-{target.id}",
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source="standard",
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severity="alert",
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category="availability",
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name="Target Reachability",
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description="Verifies that the monitored database can be reached by the collector.",
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target_id=target.id,
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target_name=target.name,
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value=None,
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warning_threshold=None,
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alert_threshold=None,
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comparison="gte",
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message=f"Connection failed: {exc}",
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checked_at=checked_at,
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)
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)
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finally:
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if conn:
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await conn.close()
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# 2) Collector freshness based on latest stored metric.
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latest_ts = await db.scalar(select(func.max(Metric.ts)).where(Metric.target_id == target.id))
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if latest_ts is None:
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forced_items.append(
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AlertStatusItem(
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alert_key=f"std-metric-freshness-{target.id}",
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source="standard",
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severity="warning",
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category="availability",
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name="Collector Freshness",
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description="Ensures fresh metrics are arriving for the target.",
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target_id=target.id,
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target_name=target.name,
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value=None,
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warning_threshold=None,
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alert_threshold=None,
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comparison="gte",
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message="No metrics collected yet for this target.",
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checked_at=checked_at,
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)
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)
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else:
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age_seconds = max(0.0, (checked_at - latest_ts).total_seconds())
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rules.append(
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_RuleInput(
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key="collector_freshness_seconds",
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name="Collector Freshness",
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description="Age of the most recent metric sample.",
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category="availability",
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value=age_seconds,
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warning_threshold=float(settings.poll_interval_seconds * 2),
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alert_threshold=float(settings.poll_interval_seconds * 4),
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)
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)
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active_connections = await _latest_metric_value(db, target.id, "connections_active")
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total_connections = await _latest_metric_value(db, target.id, "connections_total")
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cache_hit_ratio = await _latest_metric_value(db, target.id, "cache_hit_ratio")
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lock_count = await _latest_metric_value(db, target.id, "locks_total")
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checkpoints_req_delta = await _metric_delta(db, target.id, "checkpoints_req", minutes=15)
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deadlocks_delta = await _metric_delta(db, target.id, "deadlocks", minutes=60)
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slowest_query_mean = await _latest_query_snapshot_max(db, target.id, "mean_time")
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slowest_query_total = await _latest_query_snapshot_max(db, target.id, "total_time")
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active_ratio = None
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if (
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active_connections is not None
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and total_connections is not None
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and total_connections >= settings.alert_active_connection_ratio_min_total_connections
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):
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active_ratio = active_connections / total_connections
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rollback_ratio_window = settings.alert_rollback_ratio_window_minutes
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rollback_ratio_val, tx_total_window, rollback_count_window = await _rollback_ratio_recent(
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db,
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target.id,
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minutes=rollback_ratio_window,
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min_total_transactions=settings.alert_rollback_ratio_min_total_transactions,
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min_rollbacks=settings.alert_rollback_ratio_min_rollbacks,
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)
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rules.extend(
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[
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_RuleInput(
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key="active_connections_ratio",
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name="Active Connection Ratio",
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description=(
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"Share of active sessions over total sessions. "
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f"Only evaluated when total sessions >= {settings.alert_active_connection_ratio_min_total_connections}."
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),
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category="capacity",
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value=active_ratio,
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warning_threshold=0.70,
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alert_threshold=0.90,
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),
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_RuleInput(
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key="cache_hit_ratio_low",
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name="Cache Hit Ratio",
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description="Low cache hit ratio means increased disk reads and slower queries.",
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category="performance",
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value=cache_hit_ratio,
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warning_threshold=0.95,
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alert_threshold=0.90,
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comparison="lte",
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),
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_RuleInput(
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key="locks_total",
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name="Lock Pressure",
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description="Number of locks currently held on the target.",
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category="contention",
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value=lock_count,
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warning_threshold=50,
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alert_threshold=100,
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),
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_RuleInput(
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key="checkpoints_req_15m",
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name="Checkpoint Pressure (15m)",
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description="Increase of requested checkpoints in the last 15 minutes.",
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category="io",
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value=checkpoints_req_delta,
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warning_threshold=5,
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alert_threshold=15,
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),
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_RuleInput(
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key="rollback_ratio",
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name="Rollback Ratio",
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description=(
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f"Fraction of rolled back transactions in the last {rollback_ratio_window} minutes "
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f"(evaluated only when at least {settings.alert_rollback_ratio_min_total_transactions} "
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f"transactions and {settings.alert_rollback_ratio_min_rollbacks} rollbacks occurred)."
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),
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category="transactions",
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value=rollback_ratio_val,
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warning_threshold=0.10,
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alert_threshold=0.25,
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),
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_RuleInput(
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key="deadlocks_60m",
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name="Deadlocks (60m)",
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description="Increase in deadlocks during the last hour.",
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category="contention",
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value=deadlocks_delta,
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warning_threshold=1,
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alert_threshold=5,
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),
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_RuleInput(
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key="slowest_query_mean_ms",
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name="Slowest Query Mean Time",
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description="Highest mean execution time in the latest query snapshot.",
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category="query",
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value=slowest_query_mean,
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warning_threshold=300,
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alert_threshold=1000,
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),
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_RuleInput(
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key="slowest_query_total_ms",
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name="Slowest Query Total Time",
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description="Highest total execution time in the latest query snapshot.",
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category="query",
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value=slowest_query_total,
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warning_threshold=3000,
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alert_threshold=10000,
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),
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]
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)
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# Expose transaction volume as contextual metric for UI/debugging.
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rules.append(
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_RuleInput(
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key="rollback_tx_volume_15m",
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name="Rollback Ratio Evaluation Volume",
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description=f"Total transactions in the last {rollback_ratio_window} minutes used for rollback-ratio evaluation.",
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category="transactions",
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value=tx_total_window,
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warning_threshold=None,
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alert_threshold=None,
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)
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)
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rules.append(
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_RuleInput(
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key="rollback_count_window",
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name="Rollback Count (Window)",
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description=f"Rollback count in the last {rollback_ratio_window} minutes used for rollback-ratio evaluation.",
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category="transactions",
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value=rollback_count_window,
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warning_threshold=None,
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alert_threshold=None,
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)
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)
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return rules, forced_items
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async def _evaluate_standard_alerts(db: AsyncSession, targets: list[Target]) -> list[AlertStatusItem]:
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checked_at = datetime.now(timezone.utc)
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items: list[AlertStatusItem] = []
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for target in targets:
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rules, forced_items = await _build_standard_rules(db, target)
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items.extend(forced_items)
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for rule in rules:
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severity = _severity_from_thresholds(rule.value, rule.comparison, rule.warning_threshold, rule.alert_threshold)
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if severity not in {"warning", "alert"}:
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continue
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items.append(
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AlertStatusItem(
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alert_key=f"std-{rule.key}-{target.id}",
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source="standard",
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severity=severity,
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category=rule.category,
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name=rule.name,
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description=rule.description,
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target_id=target.id,
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target_name=target.name,
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value=rule.value,
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warning_threshold=rule.warning_threshold,
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alert_threshold=rule.alert_threshold,
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comparison=rule.comparison,
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message=_status_message(rule.value, rule.comparison, rule.warning_threshold, rule.alert_threshold),
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checked_at=checked_at,
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)
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)
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return items
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async def _evaluate_custom_alerts(db: AsyncSession, targets: list[Target]) -> list[AlertStatusItem]:
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checked_at = datetime.now(timezone.utc)
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defs = (
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await db.scalars(select(AlertDefinition).where(AlertDefinition.enabled.is_(True)).order_by(desc(AlertDefinition.id)))
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).all()
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target_by_id = {t.id: t for t in targets}
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items: list[AlertStatusItem] = []
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for definition in defs:
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target_candidates = targets if definition.target_id is None else [target_by_id.get(definition.target_id)]
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for target in [t for t in target_candidates if t is not None]:
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value: float | None = None
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severity = "unknown"
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message = "No data"
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try:
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value = await run_scalar_sql_for_target(target, definition.sql_text)
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severity = _severity_from_thresholds(
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value=value,
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comparison=definition.comparison,
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warning_threshold=definition.warning_threshold,
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alert_threshold=definition.alert_threshold,
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)
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message = _status_message(value, definition.comparison, definition.warning_threshold, definition.alert_threshold)
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except Exception as exc:
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severity = "alert"
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message = f"Execution failed: {exc}"
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if severity not in {"warning", "alert"}:
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continue
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items.append(
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AlertStatusItem(
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alert_key=f"custom-{definition.id}-{target.id}",
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source="custom",
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severity=severity,
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category="custom",
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name=definition.name,
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description=definition.description or "Custom SQL alert",
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target_id=target.id,
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target_name=target.name,
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value=value,
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warning_threshold=definition.warning_threshold,
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alert_threshold=definition.alert_threshold,
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comparison=definition.comparison,
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message=message,
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checked_at=checked_at,
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sql_text=definition.sql_text,
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)
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)
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return items
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async def get_alert_status(db: AsyncSession, use_cache: bool = True) -> AlertStatusResponse:
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now_seconds = time.time()
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cached = _status_cache.get("data")
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expires = float(_status_cache.get("expires", 0.0))
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if use_cache and cached and expires > now_seconds:
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return cached
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targets = (await db.scalars(select(Target).order_by(Target.name.asc()))).all()
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standard_items = await _evaluate_standard_alerts(db, targets)
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custom_items = await _evaluate_custom_alerts(db, targets)
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all_items = standard_items + custom_items
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warnings = [item for item in all_items if item.severity == "warning"]
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alerts = [item for item in all_items if item.severity == "alert"]
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warnings.sort(key=lambda i: (i.target_name.lower(), i.name.lower()))
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alerts.sort(key=lambda i: (i.target_name.lower(), i.name.lower()))
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payload = AlertStatusResponse(
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generated_at=datetime.now(timezone.utc),
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warnings=warnings,
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alerts=alerts,
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warning_count=len(warnings),
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alert_count=len(alerts),
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)
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_status_cache["data"] = payload
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_status_cache["expires"] = now_seconds + _STATUS_CACHE_TTL_SECONDS
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return payload
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