How the Cloudflare global network optimizes for system reboots during low-traffic periods

This post details the automation of determining data center maintenance windows for server reboots. Previously a manual SRE task, the process now uses sinusoidal wave fitting on historical CPU traffic data to identify low-traffic periods. The implementation uses Python with scipy.optimize.curve_fit, estimating amplitude, frequency, phase, and offset. The system caches these windows in Consul and includes fallback mechanisms for data centers with insufficient data or non-sinusoidal patterns. Goodness of fit is calculated using chi-squared to assess accuracy.