中国科学院深圳先进技术研究院机构知识库(SIAT OpenIR): Imbalance in the Cloud: an Analysis on Alibaba Cluster Trace
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Imbalance in the Cloud: an Analysis on Alibaba Cluster Trace
Chengzhi Lu; Kejiang Ye; Guoyao Xu; Cheng-Zhong Xu; Tongxin Bai
2017
Conference NameBig Data 2017
Conference Date2017
Conference Place美国
Other AbstractAbstract—To improve resource efficiency and design intelligent scheduler for clouds, it is necessary to understand the workload characteristics and machine utilization in large-scale cloud data centers. In this paper, we perform a deep analysis on a newly released trace dataset by Alibaba in September 2017, consists of detail statistics of 11089 online service jobs and 12951 batch jobs co-locating on 1300 machines over 12 hours. To the best of our knowledge, this is one of the first work to analyze the Alibaba public trace. Our analysis reveals several important insights about different types of imbalance in the Alibaba cloud. Such imbalances exacerbate the complexity and challenge of cloud resource management, which might incur severe wastes of resources and low cluster utilization. 1) Spatial Imbalance: heterogeneous resource utilization across machines and workloads. 2) Temporal Imbalance: greatly time-varying resource usages per workload and machine. 3) Imbalanced proportion of multi-dimensional resources (CPU and memory) utilization per workload. 4) Imbalanced resource demands and runtime statistics (duration and task number) between online service and offline batch jobs. We argue accommodating such imbalances during resource allocation is critical to improve cluster efficiency, and will motivate the emergence of new resource managers and schedulers.
Department云计算
Indexed ByEI
Language英语
Document Type会议论文
Identifierhttp://ir.siat.ac.cn/handle/172644/12667
Collection数字所
Affiliation2017
Recommended Citation
GB/T 7714
Chengzhi Lu,Kejiang Ye,Guoyao Xu,et al. Imbalance in the Cloud: an Analysis on Alibaba Cluster Trace[C],2017.
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