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Today's clusters often have to divide resources among a diverse set of jobs.These jobs are heterogeneous both in execution time and in their rate ofarrival. Execution time heterogeneity has lead to the development of hybridschedulers that can schedule both short and long jobs to ensure good taskplacement. However, arrival rate heterogeneity, or burstiness, remains aproblem in existing schedulers. These hybrid schedulers manage resources onstatically provisioned cluster, which can quickly be overwhelmed by bursts inthe number of arriving jobs.  In this paper we propose CloudCoaster, a hybrid scheduler that dynamicallyresizes the cluster by leveraging cheap transient servers. CloudCoasterschedules jobs in an intelligent way that increases job performance whilereducing overall resource cost. We evaluate the effectiveness of CloudCoasterthrough simulations on real-world traces and compare it against a state-of-arthybrid scheduler. CloudCoaster improves the average queueing delay time ofshort jobs by 4.8X while maintaining long job performance. In addition,CloudCoaster reduces the short partition budget by over 29.5%.

CloudCoaster: Transient-aware Bursty Datacenter Workload Scheduling