Splunk Inc.
Processing data streams received from instrumented software using incremental finite window double exponential smoothing

Abstract:

A system receives a time series of data values from instrumented software executing on an external system. Each data value corresponds to a metric of the external system. The system stores a level value representing a current estimate of the time series and a trend value representing a trend in the time series. The level and trend values are based on data in a window having a trailing value. In response to receiving a most recent value, the system updates the level value and the trend value to add an influence of the most recent value and remove an influence of the trailing value. The system forecasts based on the updated level and trend values, and in response to determining that the forecast indicates the potential resource shortage event, takes action.