Storage Sharing Optimization Under Constraints of SLO Compliance and Performance Variability

Abstract

SLO enforcement with the required strong SLO compliance and the desired low level of performance variability is necessary to ensure QoS for user applications with precisely differentiated service levels. However, for the cloud consolidating a large number of VMs rented by users, it is a great challenge to formulate an IO capacity allocation among consolidated VMs under the user-customized QoS constraints of SLO compliance and performance fluctuation for consolidated VMs. To address this challenge, we propose SASLO, an end-to-end VM-oriented control framework that supports users in customizing SLO targets and QoS constraints for each VM. SASLO can dynamically coordinate the throughput target and IO size limit for each VM adapting to the status of SLO enforcement so as to maximize the IO capacity allocation among consolidated VMs under QoS constraints. To accurately enforce time-varying throughput target, SASLO establishes a proportional-integral IO controller for each individual VM to converge the actual throughput to the target with an expected settling time. Our extensive evaluation driven by representative benchmarks demonstrates that SASLO is able to formulate a satisfactory IO capacity allocation plan for consolidated VMs under the constraints of SLO compliance and performance variability.