Cloud computing in general, and Infrastructure-as-a-Service (IaaS) in particular, have become widely accepted and adopted paradigms for computing with the offerings of virtual machines (VM) on demand. By 2020, 67% of enterprise IT infrastructure and software spending will be for cloud-based offerings.16
A major factor in the increased adoption of the cloud by enterprise IT was its pay-as-you-go model where a customer pays only for resources leased from the cloud provider and have the ability to get as many resources as needed with no up-front cost (elasticity).2 Unfortunately, the burden of scaling was left for developers and system designers that typically used overprovisioning techniques to handle sudden surges in service requests. Studies of reported usage of cloud resources in datacenters19 show a substantial gap between the resources that cloud customers allocate and pay for (leasing VMs), and actual resource utilization (CPU, memory, and so on).
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