rcourtman f7bb6d5446 feat(ai): implement metric-specific anomaly thresholds ... Smarter anomaly detection to reduce false positives: **Learning Window:** 7 days → 14 days - Captures weekly patterns (weekday vs weekend) **Metric-Specific Thresholds:** CPU: - Only report if usage >70% AND >2x baseline - Low CPU variance (5% vs 10%) is not actionable Memory: - Report if >80% OR (>1.5x baseline AND >60%) - Memory is more stable, lower threshold makes sense Disk: - Report if >85% usage OR +15 percentage points growth - Disk problems are critical, use absolute thresholds Other metrics: - Use 2x threshold as default This dramatically reduces 'noise' anomalies while catching actual problems that need operator attention.		2025-12-21 17:31:30 +00:00
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store.go	feat(ai): implement metric-specific anomaly thresholds	2025-12-21 17:31:30 +00:00
store_extended_test.go	Add comprehensive AI test coverage	2025-12-16 12:33:06 +00:00
store_test.go	test(baseline): add tests for trend prediction	2025-12-21 11:31:58 +00:00