fix(vin-anomaly): volume_drop'u sürdürülebilir + haftanın-günü-duyarlı yap

volume_drop iki nedenle false-positive üretiyordu (2026-06-14 Pazar, decode
tamamen çalışırken saatte bir −%100 "kesinti" bastı):
1. Tek 15dk pencere — düşük B2B decode trafiği patlamalı (bir kullanıcı birkaç
   sorgu yapar, sonra bir saat sessizlik), tek bir 0 penceresi sağlıklıyken bile
   normal.
2. Ardışık-7-gün baseline — decode talebinde güçlü haftalık mevsimsellik var
   (hafta sonu sakin); 7 gün baseline yoğun hafta içini hafta sonu beklentisine
   katlıyor → normal bir Pazar (~1-2/saat) hafta-içi-şişmiş ~18/saat baseline'a
   karşı −%100 okunuyor.

Düzeltme: volume_drop artık SON 1 SAATİ, AYNI GÜN/AYNI SAAT son 4 haftanın
ortalamasına karşı değerlendiriyor; yalnız o gün/saat tarihsel olarak gerçek
hacim görüyorsa (≥12/saat) ve son saat bunun ≥%80 altındaysa tetikleniyor.
Hafta sonu saatleri aynı-gün baseline'ı eşiğin altında kaldığı için kendiliğinden
susuyor; gerçek bir hafta-içi-yoğun-saat çöküşü hâlâ tetikliyor (prod query_logs
ile doğrulandı: bugünün Pazar saatleri SUSUYOR, Çarşamba 13:00 ~13/saat hâlâ izleniyor).

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

apps/web/src/lib/sase/vin-anomaly.ts

@@ -9,9 +9,21 @@ const MIN_CURRENT_VOLUME = 5; // skip checks that need volume to be meaningful
 // volume_spike and unknown_vin_spike (seen 2026-06-11: one user retrying one
 // catalogless Toyota VIN). Require at least this many distinct users.
 const MIN_DISTINCT_USERS = 2;
-// volume_drop needs a meaningful expected volume — at ~2.5 expected/window
+// volume_drop is evaluated over a TRAILING HOUR against a DAY-OF-WEEK-aware
-// (night hours) a single quiet window reads as a −100% outage.
+// baseline. Two failure modes of the old single-15min, consecutive-7-day version
-const MIN_EXPECTED_PER_WINDOW = 4;
+// (both seen 2026-06-14, a Sunday): (1) low B2B decode traffic is bursty, so a
+// lone 15-min window at 0 is normal even when healthy; (2) decode demand has
+// strong weekly seasonality (quiet weekends), so a 7-consecutive-day baseline
+// folds busy weekdays into a weekend expectation — a normal Sunday (~1-2/hr)
+// read as a −100% drop vs a weekday-inflated ~18/hr baseline. The hour window
+// fixes (1); the same-weekday baseline fixes (2).
+const HOUR_WINDOW_MIN = 60;
+// Compare against the same weekday + same hour over the last N weeks.
+const DOW_BASELINE_WEEKS = 4;
+// Below this expectation the (same-weekday) hour is too thin for a "drop" to
+// mean anything — skip volume_drop. Naturally excludes quiet weekend hours,
+// whose same-weekday baseline sits well under it.
+const MIN_EXPECTED_PER_HOUR = 12;
 // success_rate_drop is a RATE over a tiny window (~2.6 decodes/15min). It must
 // see enough DISTINCT (user,vin) lookups that aren't coverage gaps before a
 // "rate" means anything — otherwise one user retrying one catalogless VIN reads
@@ -255,6 +267,25 @@ async function windowStats(start: Date, end: Date): Promise<WindowStats> {
  * For "now is 14:32–14:47", we pull 14:32–14:47 from each of yesterday and
  * the prior 6 days. Average the per-day stats.
  */
+/**
+ * Expected decode volume for the trailing hour, averaged over the same hour on
+ * the same weekday across the last DOW_BASELINE_WEEKS weeks. Unlike
+ * baselineStats this includes zero-volume samples (a genuinely quiet weekend
+ * hour IS the expectation, not noise to drop) — that's what makes weekend hours
+ * fall below MIN_EXPECTED_PER_HOUR and self-suppress.
+ */
+async function dowHourlyExpected(now: Date): Promise<number> {
+  const totals: number[] = [];
+  for (let w = 1; w <= DOW_BASELINE_WEEKS; w++) {
+    const end = new Date(now.getTime() - w * 7 * 24 * 60 * 60_000);
+    const start = new Date(end.getTime() - HOUR_WINDOW_MIN * 60_000);
+    const s = await windowStats(start, end);
+    totals.push(s.total);
+  }
+  if (totals.length === 0) return 0;
+  return totals.reduce((a, b) => a + b, 0) / totals.length;
+}
+
 async function baselineStats(currentEnd: Date): Promise<WindowStats> {
   const samples: WindowStats[] = [];
   for (let dayOffset = 1; dayOffset <= BASELINE_DAYS; dayOffset++) {
@@ -350,10 +381,13 @@ export async function detectVinAnomalies(): Promise<{
 }> {
   const now = new Date();
   const currentStart = new Date(now.getTime() - CURRENT_WINDOW_MIN * 60_000);
+  const hourStart = new Date(now.getTime() - HOUR_WINDOW_MIN * 60_000);
 
-  const [current, baseline] = await Promise.all([
+  const [current, baseline, hourCurrent, expectedPerHour] = await Promise.all([
     windowStats(currentStart, now),
     baselineStats(now),
+    windowStats(hourStart, now),
+    dowHourlyExpected(now),
   ]);
 
   const hits: AnomalyHit[] = [];
@@ -428,26 +462,23 @@ export async function detectVinAnomalies(): Promise<{
     }
   }
 
-  // 3. Volume drop: >= 80% below baseline (high), >= 95% (critical) — outage signal
+  // 3. Volume drop — SUSTAINED (trailing hour, not a bursty 15-min window) and
-  if (baseline.total >= MIN_BASELINE_VOLUME) {
+  //    DAY-OF-WEEK-aware (same weekday baseline, so weekends don't read as an
-    const expectedPerWindow = baseline.total / BASELINE_DAYS;
+  //    outage). Fires only when this same-weekday hour historically sees real
-    if (
+  //    volume (≥ MIN_EXPECTED_PER_HOUR) and the last hour is ≥80% below it.
-      expectedPerWindow >= MIN_EXPECTED_PER_WINDOW &&
+  if (expectedPerHour >= MIN_EXPECTED_PER_HOUR && hourCurrent.total / expectedPerHour <= 0.2) {
-      current.total / expectedPerWindow <= 0.2
+    const dropPct = (1 - hourCurrent.total / expectedPerHour) * 100;
-    ) {
+    hits.push({
-      const dropPct = (1 - current.total / expectedPerWindow) * 100;
+      type: "volume_drop",
-      hits.push({
+      severity: dropPct >= 95 ? "critical" : "high",
-        type: "volume_drop",
+      message: `Sorgu hacmi (son 60dk) ${expectedPerHour.toFixed(0)} → ${hourCurrent.total} (−${dropPct.toFixed(0)}%, aynı gün/saat ${DOW_BASELINE_WEEKS}hf ort.)`,
-        severity: dropPct >= 95 ? "critical" : "high",
+      baseline: expectedPerHour,
-        message: `Sorgu hacmi ${expectedPerWindow.toFixed(0)} → ${current.total} (−${dropPct.toFixed(0)}%, son ${CURRENT_WINDOW_MIN}dk)`,
+      observed: hourCurrent.total,
-        baseline: expectedPerWindow,
+      current_volume: hourCurrent.total,
-        observed: current.total,
+      baseline_volume: Math.round(expectedPerHour),
-        current_volume: current.total,
+      detected_at: ts,
-        baseline_volume: baseline.total,
+      dedupe_key: `vin:volume_drop:${bucket}`,
-        detected_at: ts,
+    });
-        dedupe_key: `vin:volume_drop:${bucket}`,
-      });
-    }
   }
 
   // 4. Volume spike: 5x baseline — fraud or viral. One user's retry burst is