Elastic provisioning for cloud databases with uncertainty management

Cloud computing is a compelling, emerging paradigm that supports on-demand services with pay-as-you-go model. It is fundamental for cloud providers to allocate resource quantities suitable to ensure performance while reducing the operational costs related to both overprovisioning and penalties for SLA violations. Performance of cloud services may be unstable because of the environment. Most automatic provisioning techniques lack the capacity to handle the uncertainty of service performance. In this work, we investigate uncertainty management for cloud database elasticity from a probabilistic, performance-driven standpoint, and propose ProDBC, a novel approach for elastic provisioning. ProDBC uses a separate network for profiling in order to build a probabilistic model describing the relationship between workload, resource quantities and the subsequent performance. This model is embedded into a cost function in which the trade-off between infrastructure cost, SLA violation rate and the confidence level (uncertainty) is controlled intuitively. Experimental results obtained with the OLTP Database Benchmark showed provisioning actions taken by ProDBC provides elasticity while limiting the number of SLA violations.