一句话：提出 QoS 感知资源管理器 PARTIES，使任意数量延迟关键交互服务共享物理节点而不违反 QoS，并提升吞吐。
现代数据中心多租通常只允许一个延迟关键交互服务与一个或多个低优先级尽力而为作业共置，限制了多租效率；随着云应用从批处理转向严格延迟服务，这一问题更加突出。本文提出 PARTIES，一个 QoS 感知资源管理器，使任意数量的交互式延迟关键服务能够共享同一物理节点而不违反 QoS。PARTIES 利用一组硬件与软件资源划分机制，在运行时动态调整资源分配，以满足每个共调度负载的 QoS 要求并最大化整机吞吐。作者在先进服务器平台和多种交互服务上评估，结果显示，相比现有资源管理器，PARTIES 在满足 QoS 的前提下平均提升吞吐 61%，且提升幅度随每台物理主机共调度应用数量增加而增大。
Multi-tenancy in modern datacenters is currently limited to a single latency-critical, interactive service, running alongside one or more low-priority, best-effort jobs. This limits the efficiency gains from multi-tenancy, especially as an increasing number of cloud applications are shifting from batch jobs to services with strict latency requirements. We present PARTIES, a QoS-aware resource manager that enables an arbitrary number of interactive, latency-critical services to share a physical node without QoS violations. PARTIES leverages a set of hardware and software resource partitioning mechanisms to adjust allocations dynamically at runtime, in a way that meets the QoS requirements of each co-scheduled workload, and maximizes throughput for the machine. We evaluate PARTIES on state-of-the-art server platforms across a set of diverse interactive services. Our results show that PARTIES improves throughput under QoS by 61% on average, compared to existing resource managers, and that the rate of improvement increases with the number of co-scheduled applications per physical host.