Capacity Planning and Demand Forecasting Cheat Sheet

Capacity planning and demand forecasting is the discipline of predicting how much load a system will face and provisioning just enough compute, storage, and network resources to serve it reliably, sitting squarely inside site reliability engineering alongside monitoring and incident response. It exists because both ends of the sizing problem are costly: too little capacity and a system falls over the moment traffic spikes, taking availability and revenue with it; too much and the organization burns money on idle headroom that never gets used. The non-obvious part is that most systems don't fail by running out of raw resources gradually — they fail suddenly, because queueing latency is nonlinear near saturation: a service running comfortably at 60% utilization can look nearly identical to one at 85%, right up until a small traffic bump pushes it past the knee of the curve and response times explode. Good capacity planning treats forecasting, load testing, autoscaling, and cost as one connected feedback loop rather than four separate jobs, and revisits that loop on a fixed cadence instead of only after an outage forces the question.