Robust forecasting techniques with reduced sensitivity to anomalous data

A computer-implemented method of computing a forecast F(t+x) of a metric associated with a monitored computer system for a forecast time t+x, the method comprising:

• obtaining a plurality of forecasts of the metric associated with the monitored computer system for the forecast time t+x, where the plurality includes forecasts based on observations of the monitored computer system ending at different times;
• comparing at least a portion of the obtained forecasts to each other;
• selecting at least a portion of the obtained forecasts for computation of the forecast F(t+x) at least partially in response to the comparison the computation of the forecast F(t+x) performed by execution of software by one or more processors;
• and
• using the computed forecast F(t+x) at least in part for detecting an anomaly associated with the monitored computer system.

A system for monitoring a monitored computer system, the monitoring system comprising:

• a computer memory configured to store one or more program modules for computing a forecast F(t+x) of a metric of the monitored computer system for a forecast time t+x;
• a processor configured to communicate with the computer memory, the processor configured to execute the one or more program modules stored on the computer memory, the program modules configured to:
• generate a first forecast F1(t+x) of the metric of the monitored computer system for the forecast time t+x at least partially based on an observation y(t) of the monitored computer system from a first time t earlier in time to the forecast time t+x;
• obtain one or more supplemental forecasts of the metric of the monitored computer system also for the forecast time t+x, where each of the one or more supplemental forecasts are based on data ending earlier in time than the first time t;
• and
• determine a value for the forecast F(t+x) from the first forecast F1(t+x) and the one or more supplemental forecasts.