  At eBay, there are thousands of product health metrics for different domain
teams to monitor. We built a two-phase alerting system to notify users with
actionable alerts based on anomaly detection and alert retrieval. In the first
phase, we developed an efficient anomaly detection algorithm, called Moving
Metric Detector (MMD), to identify potential alerts among metrics with
distribution agnostic criteria. In the second alert retrieval phase, we built
additional logic with feedbacks to select valid actionable alerts with
point-wise ranking model and business rules. Compared with other trend and
seasonality decomposition methods, our decomposer is faster and better to
detect anomalies in unsupervised cases. Our two-phase approach dramatically
improves alert precision and avoids alert spamming in eBay production.
