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Online media offers opportunities to marketers to deliver brand messages to alarge audience. Advertising technology platforms enables the advertisers tofind the proper group of audiences and deliver ad impressions to them in realtime. The recent growth of the real time bidding has posed a significantchallenge on monitoring such a complicated system. With so many components weneed a reliable system that detects the possible changes in the system andalerts the engineering team. In this paper we describe the mechanism that weinvented for recovering the representative metrics and detecting the change intheir behavior. We show that this mechanism is able to detect the possibleproblems in time by describing some incident cases.

Finding Needle in a Million Metrics: Anomaly Detection in a Large-scale Computational Advertising Platform