In Datacenter Performance, the only Constant Is Change

Dmitry Duplyakin, Alexandru Uta, Aleksander Maricq, Robert Ricci

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademicpeer-review


All computing infrastructure suffers from performance variability, be it bare-metal or virtualized. This phenomenon originates from many sources: some transient, such as noisy neighbors, and others more permanent but sudden, such as changes or wear in hardware, changes in the underlying hypervisor stack, or even undocumented interactions between the policies of the computing resource provider and the active workloads. Thus, performance measurements obtained on clouds, HPC facilities, and, more generally, datacenter environments are almost guaranteed to exhibit performance regimes that evolve over time, which leads to undesirable nonstationarities in application performance. In this paper, we present our analysis of performance of the bare-metal hardware available on the CloudLab testbed where we focus on quantifying the evolving performance regimes using changepoint detection. We describe our findings, backed by a dataset with nearly 6.9M benchmark results collected from over 1600 machines over a period of 2 years and 9 months. These findings yield a comprehensive characterization of real-world performance variability patterns in one computing facility, a methodology for studying such patterns on other infrastructures, and contribute to a better understanding of performance variability in general.

Original languageEnglish
Title of host publication2020 20th IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing (CCGRID)
Subtitle of host publicationProceedings
EditorsLaurent Lefevre, Carlos A. Varela, George Pallis, Adel N. Toosi, Omer Rana, Rajkumar Buyya
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages10
ISBN (Electronic)9781728160955
Publication statusPublished - 14 Jul 2020
Event20th IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing, CCGRID 2020 - Melbourne, Australia
Duration: 11 May 202014 May 2020


Conference20th IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing, CCGRID 2020


ACKNOWLEDGMENTS This material in this paper is based upon work supported by the National Science Foundation, Grant Number 1743363.

FundersFunder number
National Science Foundation
Directorate for Computer and Information Science and Engineering1743363


    • Benchmarking
    • Changepoint Detection
    • Datacenter Performance
    • Temporal Analysis
    • Variability


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