Detecting Anomalies in Time Series Data

Disclosed are various embodiments for detecting anomalies in time series data. At least one anomaly is detected in a time series that is derived from a corresponding metric observed from a computing system. The time series is non-stationary time series or heteroskedastic. The detected anomaly is correlated with at least one of a plurality of external events affecting the computing system. A magnitude is assigned to the detected anomaly. The detected one anomaly, the assigned magnitude, and the correlated at least one external event are reported to a client device.