GPU capacity management across clouds
Buy GPUs like a portfolio: on-demand, committed, spot and owned capacity; the effective-price maths of commitments; forecasting and lead times; quotas; keeping workloads portable across providers; avoiding egress and data-gravity traps; and operating a multi-provider fleet without losing control.
GPU capacity is not like CPU capacity. You cannot always get the instance you want, where you want it, at the price you want, when you need it. Supply is constrained, hardware generations change quickly, and prices vary between providers by large factors. Teams that run inference at scale therefore manage GPUs the way finance teams manage investments: as a portfolio with different instruments, risks and horizons.
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