Anomaly Detection Brief

Write an anomaly detection brief for monitoring [METRIC_OR_SYSTEM — e.g., daily revenue / API error rate / user sign-ups] at [COMPANY_NAME]. The goal is to automatically flag when something is wrong so the team can investigate before customers are impacted. The brief must cover: (1) Metric definition — exact calculation of the metric being monitored and its data source, (2) Baseline behavior — describe the expected patterns: typical range [EXPECTED_RANGE], known seasonality (day-of-week, monthly cycles, holidays), and trend direction, (3) Anomaly types to detect — for each of the following anomaly types: spike, drop, gradual drift, and missing data — define what constitutes an anomaly (e.g., "a drop of more than 20% versus the same day last week"), (4) Detection method — recommend a specific statistical method (e.g., Z-score, IQR, EWMA, Prophet) appropriate for this metric's characteristics and explain why, (5) Alerting logic — alert threshold, cooldown period to prevent alert fatigue, and who gets notified via [NOTIFICATION_CHANNEL], (6) Triage runbook — a 5-step investigation checklist for the on-call engineer when an anomaly fires. Context: [ADDITIONAL_CONTEXT].