Evaluating Docker storage performance: from workloads to graph drivers

Vasily Tarasov, Lukas Rupprecht, Dimitris Skourtis, Wenji Li, Raju Rangaswami, Ming Zhao

Research output: Contribution to journalArticle

2 Scopus citations

Abstract

Containers are a widely successful technology today popularized by Docker. They improve system utilization by increasing workload density and enable seamless deployment of workloads across development, test, and production environments. Docker’s unique approach to data management, which involves frequent snapshot creation and removal, presents a new set of exciting challenges for storage systems. At the same time, storage management for Docker containers has remained largely unexplored with a dizzying array of solution choices and configuration options. In this paper we unravel the multi-faceted nature of Docker storage and demonstrate its impact on system and workload performance. As we uncover new properties of the popular Docker storage drivers, this is a sobering reminder that widespread use of new technologies can often precede their careful evaluation.

Original languageEnglish (US)
Pages (from-to)1159-1172
Number of pages14
JournalCluster Computing
Volume22
Issue number4
DOIs
StatePublished - Dec 1 2019

Keywords

  • Containers
  • Docker
  • Performance
  • Storage

ASJC Scopus subject areas

  • Software
  • Computer Networks and Communications

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    Tarasov, V., Rupprecht, L., Skourtis, D., Li, W., Rangaswami, R., & Zhao, M. (2019). Evaluating Docker storage performance: from workloads to graph drivers. Cluster Computing, 22(4), 1159-1172. https://doi.org/10.1007/s10586-018-02893-y