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One major benefit claimed for cloud computing is elasticity: the cost to a consumer of computation can grow or shrink with the workload. This paper offers improved ways to quantify the elasticity concept, using data available to the consumer. We define a measure that reflects the financial penalty to a particular consumer, from under-provisioning (leading to unacceptable latency or unmet demand) or overprovisioning (paying more than necessary for the resources needed to support a workload). We have applied several workloads to a public cloud; from our experiments we extract insights into the characteristics of a platform that influence its elasticity. We explore the impact of the rules used to increase or decrease capacity.

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