PriorityMeister: Tail Latency QoS for Shared Networked Storage

ACM Symposium on Cloud Computing 2014 (SoCC'14), Seattle, WA, Nov 2014.

Timothy Zhu, Alexey Tumanov, Michael A. Kozuch* Mor Harchol-Balter, Gregory R. Ganger

Carnegie Mellon University
Pittsburgh, PA

*Intel Labs


Meeting service level objectives (SLOs) for tail latency is an important and challenging open problem in cloud computing infrastructures. The challenges are exacerbated by burstiness in the workloads. This paper describes PriorityMeister – a system that employs a combination of per-workload priorities and rate limits to provide tail latency QoS for shared networked storage, even with bursty workloads. PriorityMeister automatically and proactively configures workload priorities and rate limits across multiple stages (e.g., a shared storage stage followed by a shared network stage) to meet end-toend tail latency SLOs. In real system experiments and under production trace workloads, PriorityMeister outperforms most recent reactive request scheduling approaches, with more workloads satisfying latency SLOs at higher latency percentiles. PriorityMeister is also robust to mis-estimation of underlying storage device performance and contains the effect of misbehaving workloads.






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Last updated 14 October, 2014