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Quick Definition
Capacity planning is the process of forecasting the compute, storage, and network resources a workload will need and provisioning accordingly. In the cloud it balances performance and cost, avoiding both shortages that hurt reliability and overprovisioning that wastes spend.
Capacity planning is the practice of estimating future infrastructure needs: how much compute, storage, and network your workloads will require next quarter or next year, and how to provision it cost-effectively.
In the cloud, the question shifts from buying hardware to choosing commitments. Plan too high and you lock in reservations you cannot use. Plan too low and everything runs at expensive on-demand rates. Good planning combines cost forecasting, growth plans from product teams, and headroom for surprises.
Example. A company expects a festival-season traffic spike of 3x for two weeks. Instead of reserving capacity for the peak all year, it commits to baseline usage and covers the spike with autoscaling and Spot capacity, paying for the peak only while it lasts.
Forecasting is planning's raw material. Start with this beginner's guide to cloud cost forecasting, then size commitments against the baseline it reveals.
On-premises planning buys hardware years ahead. Cloud planning chooses commitment levels and scaling strategies, and can be revised continuously.
Enough to absorb forecast error and short spikes, often 15 to 30 percent above baseline, covered by autoscaling rather than standing capacity.
Engineering for workload knowledge, finance for budget framing, and product for growth plans. Plans made by one group alone tend to fail.