Moving Metric Detection and Alerting System at eBay

EasyChair Preprint 3121

Abstract

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.

Keyphrases: alerting system, anomaly detection, time series decomposition

@booklet{EasyChair:3121,
  author    = {Zezhong Zhang and Keyu Nie and Ted Tao Yuan},
  title     = {Moving Metric Detection and Alerting System at eBay},
  howpublished = {EasyChair Preprint 3121},
  year      = {EasyChair, 2020}}