Storage VirtualizationCluster ComputingStorage PerformanceEngineeringEdge ComputingSoftware-defined StorageCloud ComputingStorage ManagementComputer EngineeringComputer ArchitectureVirtual Resource PartitioningParallel ProgrammingComputer ScienceStorage SystemParallel ComputingStorage ConsolidationData ManagementWorkload Consolidation
Workload consolidation is a key technique in reducing costs in virtualized datacenters. When considering storage consolidation, a key problem is the unpredictable performance behavior of consolidated workloads on a given storage system. In practice, this often forces system administrators to grossly overprovision storage to meet application demands. In this paper, we show that existing modeling techniques are inaccurate and ineffective in the face of heterogenous devices. We introduce Romano, a storage performance management system designed to optimize truly heterogeneous virtualized datacenters. At its core, Romano constructs and adapts approximate workload-specific performance models of storage devices automatically, along with prediction intervals. It then applies these models to allow highly efficient IO load balancing.
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