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A study of pricing for cloud resources

We present a study of pricing cloud resources in this position paper. Our objective is to explore and understand the interplay between economics and systems designs proposed by recent research. We develop a general model that captures the resource needs of various applications and usage pricing of cloud computing. We show that a uniform price does not suffer any revenue loss compared to first-order price discrimination. We then consider alternative strategies that a provider can use to improve revenue, including resource throttling and performance guarantees, enabled by recent technical developments. We prove that throttling achieves the maximum revenue at the expense of tenant surplus, while providing performance guarantees with an extra fee is a fairer solution for both parties. We further extend the model to incorporate the cost aspect of the problem, and the possibility of right-sizing capacity. We reveal another interesting insight that in some cases, instead of focusing on right-sizing, the provider should work on the demand and revenue side of the equation, and pricing is a more feasible and simpler solution. Our claims are evaluated through extensive trace-driven simulations with real-world workloads.