Strategic Throttling in Large Cloud Computing Platforms

Cloud platforms are critical infrastructure for digital economy. This study explains how large cloud providers use prices and service quality to allocate nonstorable computing time among customers with different willingness to pay and delay sensitivity. Pooling many uncorrelated workloads makes utilization predictable, reducing the need for idle backup capacity and improving operating efficiency. The predictability, however, allows providers to profitably throttle lower-tier customers through slower processing or higher interruption risk while keeping the whole market served. For cloud managers, the analysis shows how cross-region pooling, transparent interruption policies, and auction-based spot pricing can improve utilization, segment demand, and guide capacity planning. For customers and policymakers, the results identify why throttling persists: high switching costs and proprietary ecosystems weaken competitive pressure. Policies that improve workload portability, reduce data-egress frictions, and increase data interoperability can benefit the consumers and society without sacrificing the scale economies of large cloud networks. Structural remedies that reduce scale may curb market power but risk undermining operational efficiency.