Metrics prediction using dynamic confidence coefficients

Abstract

A method includes obtaining time series data for a usage or performance metric for computing resources in a service provider network comprising a plurality of observations recorded in a plurality of respective time steps. A prediction error is determined for a previous prediction of an observation in the time series data. The prediction error is used to update a standard deviation of a set of predication errors for the usage or performance metric. The standard deviation and the prediction error are then used to update a confidence coefficient. A prediction limit for the usage or performance metric is then determined based on an expected value, the confidence coefficient, and the standard deviation. One or more events may be generated based on the prediction limit, which may be used to trigger a reconfiguration or auto-scaling of the computing resources.