Using the Gini Coefficient to Plan Edge Capacity
Summary
Fastly explains a capacity-planning approach for edge POPs that uses the Gini coefficient to measure traffic inequality. The method links inequality to cache behavior and CPU utilization, yielding a simple, fast model for headroom and capacity placement across regions and events. It also covers baseline forecasting and scenario analysis to guide edge deployments.