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An In-depth Comparative Analysis of Cloud Block Storage Workloads: Findings and Implications

Published: 06 March 2023 Publication History

Abstract

Cloud block storage systems support diverse types of applications in modern cloud services. Characterizing their input/output (I/O) activities is critical for guiding better system designs and optimizations. In this article, 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 we 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.

References

[1]
Irfan Ahmad. 2007. Easy and efficient disk I/O workload characterization in VMware ESX server. In Proceedings of the IEEE International Symposium on Workload Characterization (IISWC’07). 149–158.
[2]
Alibaba. 2022. Alibaba Block Traces. Retrieved from https://github.com/alibaba/block-traces.
[3]
Alibaba. 2022. Alibaba Cloud Block Storage. Retrieved from https://www.alibabacloud.com/help/doc-detail/63136.htm.
[4]
Amazon. 2022. Amazon EBS. Retrieved from https://aws.amazon.com/ebs/.
[5]
Dulcardo Arteaga, Jorge Cabrera, Jing Xu, Swaminathan Sundararaman, and Ming Zhao. 2016. CloudCache: On-demand flash cache management for cloud computing. In Proceedings of the 14th USENIX Conference on File and Storage Technologies (FAST’16). 355–369.
[6]
Dulcardo Arteaga and Ming Zhao. 2014. Client-side flash caching for cloud systems. In Proceedings of the 7th ACM International Systems and Storage Conference (SYSTOR’14). 1–11.
[7]
Berk Atikoglu, Yuehai Xu, Eitan Frachtenberg, Song Jiang, and Mike Paleczny. 2012. Workload analysis of a large-scale key-value store. In Proceedings of the ACM Special Interest Group for the Computer Performance Evaluation Community (SIGMETRICS’12). 53–64.
[8]
Doug Beaver, Sanjeev Kumar, Harry C. Li, Jason Sobel, and Peter Vajgel. 2010. Finding a needle in Haystack: Facebook’s photo storage. In Proceedings of the 9th USENIX Symposium on Operating Systems Design and Implementation (OSDI’10). 47–60.
[9]
Medha Bhadkamkar, Jorge Guerra, Luis Useche, Sam Burnett, Jason Liptak, Raju Rangaswami, and Vagelis Hristidis. 2009. BORG: Block-reORGanization for self-optimizing storage systems. In Proceedings of the 7th USENIX Conference on File and Storage Technologies (FAST’09). 183–196.
[10]
Yu Cai, Yixin Luo, Erich F. Haratsch, Ken Mai, and Onur Mutlu. 2015. Data retention in MLC NAND flash memory: Characterization, optimization, and recovery. In Proceedings of the 21st IEEE International Symposium on High Performance Computer Architecture (HPCA’15). IEEE, 551–563.
[11]
Zhichao Cao, Siying Dong, Sagar Vemuri, and David H. C. Du. 2020. Characterizing, modeling, and benchmarking RocksDB key-value workloads at Facebook. In Proceedings of the 18th USENIX Conference on File and Storage Technologies (FAST’20). 209–223.
[12]
Jeremy C. W. Chan, Qian Ding, Patrick P. C. Lee, and Helen H. W. Chan. 2014. Parity logging with reserved space: Towards efficient updates and recovery in erasure-coded clustered storage. In Proceedings of the 12th USENIX Conference on File and Storage Technologies (FAST’14). 163–176.
[13]
Tzi-cker Chiueh, Weafon Tsao, Hou-Chiang Sun, Ting-Fang Chien, An-Nan Chang, and Cheng-Ding Chen. 2014. Software orchestrated flash array. In Proceedings of the 7th ACM International Systems and Storage Conference (SYSTOR’14). 1–11.
[14]
Peter Desnoyers. 2012. Analytic modeling of SSD write performance. In Proceedings of the 5th ACM International Systems and Storage Conference (SYSTOR’12). 1–10.
[15]
Shujie Han, Patrick P. C. Lee, Fan Xu, Yi Liu, Cheng He, and Jiongzhou Liu. 2021. An in-depth study of correlated failures in production SSD-based data centers. In Proceedings of the 19th USENIX Conference on File and Storage Technologies (FAST’21). 417–429.
[16]
Tyler Harter, Brandon Salmon, Rose Liu, Andrea C. Arpaci-Dusseau, and Remzi H. Arpaci-Dusseau. 2016. Slacker: Fast distribution with lazy docker containers. In Proceedings of the 14th USENIX Conference on File and Storage Technologies (FAST’16). 181–195.
[17]
Jun He, Sudarsun Kannan, Andrea C. Arpaci-Dusseau, and Remzi H. Arpaci-Dusseau. 2017. The unwritten contract of solid state drives. In Proceedings of the 12th ACM European Conference on Computer Systems (EuroSys’17). 127–144.
[18]
W. W. Hsu and A. J. Smith. 2003. Characteristics of I/O traffic in personal computer and server workloads. IBM Syst. J. 42, 2 (2003), 347–372.
[19]
Swaroop Kavalanekar, Bruce Worthington, Qi Zhang, and Vishal Sharda. 2008. Characterization of storage workload traces from production windows servers. In Proceedings of the IEEE International Symposium on Workload Characterization (IISWC’08). 119–128.
[20]
Chunghan Lee, Tatsuo Kumano, Tatsuma Matsuki, Hiroshi Endo, Naoto Fukumoto, and Mariko Sugawara. 2017. Understanding storage traffic characteristics on enterprise virtual desktop infrastructure. In Proceedings of the 10th ACM International Systems and Storage Conference (SYSTOR’17). 1–11.
[21]
Huiba Li, Yiming Zhang, Dongsheng Li, Zhiming Zhang, Shengyun Liu, Peng Huang, Zheng Qin, Kai Chen, and Yongqiang Xiong. 2019. URSA: Hybrid block storage for cloud-scale virtual disks. In Proceedings of the 14th ACM European Conference on Computer Systems (EuroSys’19). 1–17.
[22]
Jinhong Li, Qiuping Wang, Patrick P. C. Lee, and Chao Shi. 2020. An in-depth analysis of cloud block storage workloads in large scale production. In Proceedings of the IEEE International Symposium on Workload Characterization (IISWC’20). 37–47.
[23]
Qiao Li, Liang Shi, Chun Jason Xue, Kaijie Wu, Cheng Ji, Qingfeng Zhuge, and Edwin H.-M. Sha. 2016. Access characteristic guided read and write cost regulation for performance improvement on flash memory. In Proceedings of the 14th USENIX Conference on File and Storage Technologies (FAST’16). 125–132.
[24]
Ren Shuo Liu, Chia Lin Yang, and Wei Wu. 2012. Optimizing NAND flash-based SSDs via retention relaxation. In Proceedings of the 10th USENIX Conference on File and Storage Technologies (FAST’12). 1–11.
[25]
Shuyang Liu, Shucheng Wang, Qiang Cao, Ziyi Lu, Hong Jiang, Jie Yao, Yuanyuan Dong, and Puyuan Yang. 2019. Analysis of and optimization for write-dominated hybrid storage nodes in cloud. In Proceedings of ACM Symposium on Cloud Computing (SoCC’19). 403–415.
[26]
Zaoxing Liu, Zhihao Bai, Zhenming Liu, Xiaozhou Li, Changhoon Kim, Vladimir Braverman, Xin Jin, and Ion Stoica. 2019. DistCache: Provable load balancing for large-scale storage systems with distributed caching. In Proceedings of the 17th USENIX Conference on File and Storage Technologies (FAST’19). 143–157.
[27]
Stathis Maneas, Kaveh Mahdaviani, Tim Emami, and Bianca Schroeder. 2020. A study of SSD reliability in large scale enterprise storage deployments. In Proceedings of the 18th USENIX Conference on File and Storage Technologies (FAST’20). 137–149.
[28]
Dutch T. Meyer, Gitika Aggarwal, Brendan Cully, Geoffrey Lefebvre, Michael J. Feeley, Norman C. Hutchinson, and Andrew Warfield. 2008. Parallax: Virtual disks for virtual machines. In Proceedings of the 3rd ACM European Conference on Computer Systems (EuroSys’08). 41–54.
[29]
James Mickens, Edmund B. Nightingale, Jeremy Elson, Krishna Nareddy, Darren Gehring, Bin Fan, Asim Kadav, Vijay Chidambaram, and Osama Khan. 2014. Blizzard: Fast, cloud-scale block storage for cloud-oblivious applications. In Proceedings of the 11th USENIX Symposium on Networked Systems Design and Implementation (NSDI’14). 257–273.
[30]
Microsoft. 2022. MSR Cambridge Traces. Retrieved from http://iotta.snia.org/traces/388.
[31]
Changwoo Min, Kangnyeon Kim, Hyunjin Cho, Sang-Won Lee, and Young Ik Eom. 2012. SFS: Random write considered harmful in solid state drives. In Proceedings of the 10th USENIX Conference on File and Storage Technologies (FAST’12). 1–16.
[32]
Asit K. Mishra, Joseph L. Hellerstein, Walfredo Cirne, and Chita R. Das. 2010. Towards characterizing cloud backend workloads: Insights from Google compute clusters. In Proceedings of the ACM Special Interest Group for the Computer Performance Evaluation Community (SIGMETRICS’10). 34–41.
[33]
Dushyanth Narayanan, Austin Donnelly, and Antony Rowstron. 2008. Write off-loading: Practical Power Management for Enterprise Storage. In Proceedings of the 6th USENIX Conference on File and Storage Technologies (FAST’08). 253–267.
[34]
Alma Riska and Erik Riedel. 2006. Disk drive level workload characterization. In Proceedings of the USENIX Annual Technical Conference (USENIX ATC’06). 97–102.
[35]
Mendel Rosenblum and John K. Ousterhout. 1992. The design and implementation of a log-structured file system. ACM Trans. Comput. Syst. 10, 1 (1992), 26–52.
[36]
Mohit Saxena, Michael M. Swift, and Yiying Zhang. 2012. FlashTier: A lightweight, consistent and durable storage cache. In Proceedings of the 7th ACM European Conference on Computer Systems (EuroSys’12). 267–280.
[37]
Gokul Soundararajan, Vijayan Prabhakaran, Mahesh Balakrishnan, and Ted Wobber. 2010. Extending SSD lifetimes with disk-based write caches. In Proceedings of the 8th USENIX Conference on File and Storage Technologies (FAST’10). 101–114.
[38]
C. Spearman. 1987. The proof and measurement of association between two things. Amer. J. Psychol. 100, 3/4 (1987), 441–471.
[39]
Mojtaba Tarihi, Hossein Asadi, and Hamid Sarbazi-Azad. 2015. DiskAccel: Accelerating disk-based experiments by representative sampling. In Proceedings of the ACM Special Interest Group for the Computer Performance Evaluation Community (SIGMETRICS’15). 297–308.
[40]
Tencent. 2022. Tencent Block Storage. Retrieved from http://iotta.snia.org/traces/27917.
[41]
Akshat Verma, Ricardo Koller, Luis Useche, and Raju Rangaswami. 2010. SRCMap: Energy proportional storage using dynamic consolidation. In Proceedings of the 8th USENIX Conference on File and Storage Technologies (FAST’10). 267–280.
[42]
Muhammad Wajahat, Aditya Yele, Tyler Estro, Anshul Gandhi, and Erez Zadok. 2019. Distribution fitting and performance modeling for storage traces. In Proceedings of the 27th IEEE International Symposium on the Modeling, Analysis, and Simulation of Computer and Telecommunication Systems (MASCOTS’19). IEEE, 138–151.
[43]
Carl A. Waldspurger, Nohhyun Park, Alexander Garthwaite, and Irfan Ahmad. 2015. Efficient MRC construction with SHARDS. In Proceedings of the 13th USENIX Conference on File and Storage Technologies (FAST’15). 95–110.
[44]
Hua Wang, Xinbo Yi, Ping Huang, Bin Cheng, and Ke Zhou. 2018. Efficient SSD caching by avoiding unnecessary writes using machine learning. In Proceedings of the 47th ACM International Conference on Parallel Processing (ICPP’18). 1–10.
[45]
Qiuping Wang, Jinhong Li, Patrick P. C. Lee, Tao Ouyang, Chao Shi, and Lilong Huang. 2022. Separating data via block invalidation time inference for write amplification reduction in log-structured storage. In Proceedings of the 20th USENIX Conference on File and Storage Technologies (FAST’22). 429–444.
[46]
Shucheng Wang, Ziyi Lu, Qiang Cao, Hong Jiang, Jie Yao, Yuanyuan Dong, and Puyuan Yang. 2020. BCW: Buffer-controlled writes to HDDs for SSD-HDD hybrid storage server. In Proceedings of the 18th USENIX Conference on File and Storage Technologies (FAST’20). 253–266.
[47]
Jake Wires, Stephen Ingram, Zachary Drudi, Nicholas J. A. Harvey, and Andrew Warfield. 2014. Characterizing storage workloads with counter stacks. In Proceedings of the 11th USENIX Symposium on Operating Systems Design and Implementation (OSDI’14). 335–349.
[48]
Erci Xu, Mai Zheng, Feng Qin, Yikang Xu, and Jiesheng Wu. 2019. Lessons and actions: What we learned from 10K SSD-related storage system failures. In Proceedings of the USENIX Annual Technical Conference (USENIX ATC’19). 961–976.
[49]
Gala Yadgar, Moshe Gabel, Shehbaz Jaffer, and Bianca Schroeder. 2021. SSD-based workload characteristics and their performance implications. ACM Trans. Storage 17, 1 (2021), 1–26.
[50]
Jing Yang, Shuyi Pei, and Qing Yang. 2019. WARCIP: Write amplification reduction by clustering I/O pages. In Proceedings of the 12th ACM International Systems and Storage Conference (SYSTOR’19). 155–166.
[51]
Juncheng Yang, Yao Yue, and K. V. Rashmi. 2020. A large scale analysis of hundreds of in-memory cache clusters at Twitter. In Proceedings of the 14th USENIX Symposium on Operating Systems Design and Implementation (OSDI’20). 191–208.
[52]
Yu Zhang, Ping Huang, Ke Zhou, Hua Wang, Jianying Hu, Yongguang Ji, and Bin Cheng. 2020. OSCA: An online-model based cache allocation scheme in cloud block storage systems. In Proceedings of USENIX Annual Technical Conference (USENIX ATC’20). 785–798.
[53]
Yiming Zhang, Huiba Li, Shengyun Liu, Jiawei Xu, and Guangtao Xue. 2020. PBS: An efficient erasure-coded block storage system based on speculative partial writes. ACM Trans. Storage 16, 1 (2020), 1–25.
[54]
Deng Zhou, Wen Pan, Wei Wang, and Tao Xie. 2015. I/O characteristics of smartphone applications and their implications for eMMC design. In Proceedings of the IEEE International Symposium on Workload Characterization (IISWC’15). 12–21.

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      Published In

      cover image ACM Transactions on Storage
      ACM Transactions on Storage  Volume 19, Issue 2
      May 2023
      269 pages
      ISSN:1553-3077
      EISSN:1553-3093
      DOI:10.1145/3585541
      Issue’s Table of Contents

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      Published: 06 March 2023
      Online AM: 22 November 2022
      Accepted: 15 November 2022
      Revised: 01 September 2022
      Received: 10 February 2022
      Published in TOS Volume 19, Issue 2

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      Author Tags

      1. Cloud block storage
      2. trace analysis
      3. I/O characterization

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      • Alibaba Innovation Research (AIR) program and the Research Matching Grant Scheme

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