Enabling resource sharing between transactional and batch workloads using dynamic application placement
David Carrera, Małgorzata Steinder, Ian Whalley, Jordi Torres, Eduard Ayguadé · 2008
Abstract. We present a technique that enables existing middleware to fairly manage mixed workloads: batch jobs and transactional applications. The tech-nique leverages a generic application placement controller, which dynamically al-locates compute resources to application instances. The controller works towards a fairness goal while also trying to maximize individual workload performance. We use relative performance functions to drive the application placement con-troller. Such functions are derived from workload-specific performance models— in the case of transactional workloads, we use queuing theory to build the perfor-mance model. For batch workloads, we evaluate a candidate placement by calcu-lating long-term estimates of the completion times that are achievable with that placement according to a scheduling policy. In this paper, we propose a lowest rel-ative performancwe first scheduling policy as a way to also achieve fair resource allocation among batch jobs. Our technique permits collocation of the workload types on the same physical hardware, and leverages control mechanisms such as suspension and migration to perform online system reconfiguration. In our ex-periments we demonstrate that our technique maximizes mixed workload perfor-mance while providing service differentiation based on high-level performance goals. 1