Modeling virtual machine performance: challenges and approaches
ACM SIGMETRICS Performance Evaluation Review
Communications of the ACM
The SCADS director: scaling a distributed storage system under stringent performance requirements
FAST'11 Proceedings of the 9th USENIX conference on File and stroage technologies
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FAST'12 Proceedings of the 10th USENIX conference on File and Storage Technologies
A workload characterization study of the 1998 World Cup Web site
IEEE Network: The Magazine of Global Internetworking
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The increasing spread of elastic Cloud services, together with the pay-as-you-go pricing model of Cloud computing, has led to the need of an elasticity controller. The controller automatically resizes an elastic service in response to changes in workload, in order to meet Service Level Objectives (SLOs) at a reduced cost. However, variable performance of Cloud virtual machines and nonlinearities in Cloud services complicates the controller design. We present the design and evaluation of ElastMan, an elasticity controller for Cloud-based elastic key-value stores. ElastMan combines feedforward and feedback control. Feedforward control is used to respond to spikes in the workload by quickly resizing the service to meet SLOs at a minimal cost. Feedback control is used to correct modeling errors and to handle diurnal workload. We have implemented and evaluated ElastMan using the Voldemort key-value store running in a Cloud environment based on OpenStack. Our evaluation shows the feasibility and effectiveness of our approach to automation of Cloud service elasticity.