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arXiv · 1808.02919

Characterizing Co-located Datacenter Workloads: An Alibaba Case Study

Yue Cheng·Zheng Chai·Ali Anwar
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Abstract

Warehouse-scale cloud datacenters co-locate workloads with different and often complementary characteristics for improved resource utilization. To better understand the challenges in managing such intricate, heterogeneous workloads while providing quality-assured resource orchestration and user experience, we analyze Alibaba's co-located workload trace, the first publicly available dataset with precise information about the category of each job. Two types of workload---long-running, user-facing, containerized production jobs, and transient, highly dynamic, non-containerized, and non-production batch jobs---are running on a shared cluster of 1313 machines. Our multifaceted analysis reveals insights that we believe are useful for system designers and IT practitioners working on cluster management systems.

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Yue Cheng, Zheng Chai, Ali Anwar. 2018-08-08. Characterizing Co-located Datacenter Workloads: An Alibaba Case Study. https://arxiv.org/abs/1808.02919

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