Time-Sensitive Provisioning of Bare Metal Compute as a Cloud Service

A modern cloud service that is getting popular is the supply of bare metal servers on demand to consumers who need to run high-performance algorithms for short periods of time. However, provisioning-time latencies are unpredictable in bare metal commerce, primarily because suppliers cannot exploit virtualization levers to adjust and optimize capacity. This impacts bare metal service leverage because, in the face of indeterministic fulfillment times, consumers often pre-provision for peak demand, which goes against the fundamental tenets and advantages of cloud adoption. To address this, we advocate that a cloud service broker offers time-sensitive bare metal provisioning services by building and maintaining an inventory of bare metal servers. This, however, leads to inventory optimization and profit maximization problems that resemble what traditional supply chains face, but with characteristics unique to on-demand compute economics. In this paper, we build a brokered bare metal supply chain model that identifies impacting variables, their characteristics, and inter-relationships. We argue and demonstrate that, given complex inter-variable relationships and environmental uncertainties, simulation runs are needed to complete the model and yield recommendations to optimize inventory and maximize profits.