METRIC TIME SERIES CORRELATION BY OUTLIER REMOVAL BASED ON MAXIMUM CONCENTRATION INTERVAL

摘要

A correlation relationship between two metric time series is determined after removing the impact of outlying metric values (“outliers”) that are unimportant for analytical purposes. Each of the metric time series can represent values of different system metrics obtained by mining data gathered through the monitoring of cloud deployments. The outliers can be determined based on a maximum concentration interval of the data. Removing the impact of the outliers enhances the correlation of the metric time series and provides a better representation of the correlation relationship.

主权项

1. A method comprising:
determining, by a computing device, one or more first points in a first metric time series that are outliers relative to other points in the first metric time series; determining, by the computing device, one or more second points in a second metric time series that are outliers relative to other points in the second metric time series, wherein the points in the second metric time series differ from the points in the first metric time series; removing, by the computing device, the one or more first points from the first metric time series to produce a first version of the first metric time series that lacks outliers; removing, by the computing device, the one or more second points from the second metric time series to produce a first version of the second metric time series that lacks outliers; determining, by the computing device, a first correlation coefficient based on the first version of the first metric time series and the first version of the second metric time series; storing, by the computing device, the first correlation coefficient in association with the first metric time series and the second metric time series; and accessing, by the computing device, the first correlation coefficient to quantify a possible relationship between the first metric time series and the second metric time series.