ARIMA, SARIMA, and Prophet Tested for Predicting CPU and Infrastructure Spikes

A developer built a predictive health check layer for infrastructure monitoring by testing three time-series forecasting models — ARIMA, SARIMA, and Facebook Prophet — against five real-world CPU and memory usage patterns. Prophet performed best at detecting gradual trends like slow memory leaks, while SARIMA excelled at forecasting predictable daily workday spikes when given proper seasonal configuration. All three models failed to reliably predict monthly spikes unless trained on years of historical data, as too few occurrences made it impossible to distinguish a pattern from a random anomaly. Completely random traffic bursts also defeated every model, with ARIMA and SARIMA prone to misreading sudden spikes as the start of a sustained upward trend. The findings suggest that no single model fits all infrastructure scenarios, and selecting the right forecasting tool depends heavily on the specific usage pattern being monitored.