论文标题
云块存储工作负载的深入比较分析：发现和含义
An In-Depth Comparative Analysis of Cloud Block Storage Workloads: Findings and Implications
论文作者
论文摘要
云块存储系统支持现代云服务中各种类型的应用程序。表征其I/O活动对于指导更好的系统设计和优化至关重要。在本文中，我们通过从两个生产系统（Alibaba Cloud和Tencent Cloud Block存储）收集的数十亿个I/O请求的块级I/O痕迹对生产云存储工作负载进行了深入的比较分析。我们研究了他们的负载强度，空间模式和时间模式的特征。我们还将Cloud Block存储工作负载与Microsoft Research Cambridge的企业数据中心的著名公共区块级I/O工作负载进行了比较，并确定了三种痕迹来源的共同点和差异。为此，我们通过高级分析和16个发现通过有关负载强度，空间模式和时间模式的详细分析提供了6个发现。我们讨论了我们发现对云块存储系统中负载平衡，缓存效率和存储群集管理的影响。
Cloud block storage systems support diverse types of applications in modern cloud services. Characterizing their I/O activities is critical for guiding better system designs and optimizations. In this paper, we present an in-depth comparative analysis of production cloud block storage workloads through the block-level I/O traces of billions of I/O requests collected from two production systems, Alibaba Cloud and Tencent Cloud Block Storage. We study their characteristics of load intensities, spatial patterns, and temporal patterns. We also compare the cloud block storage workloads with the notable public block-level I/O workloads from the enterprise data centers at Microsoft Research Cambridge, and identify the commonalities and differences of the three sources of traces. To this end, we provide 6 findings through the high-level analysis and 16 findings through the detailed analysis on load intensity, spatial patterns, and temporal patterns. We discuss the implications of our findings on load balancing, cache efficiency, and storage cluster management in cloud block storage systems.
