Container Restart Reduction Technique in Kubernetes Using Memory Oversubscription

Taeshin Kang, Heonchang Yu, Eunyoung Lee

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper proposes a technique to mitigate container restarts in a memory oversubscription environment based on Kubernetes. The proposed technique involves identifying containers that are likely to request memory allocation on nodes experiencing high memory usage and temporarily pausing these containers. By significantly reducing the CPU usage of containers, the similar effect as pausing them can be achieved. The suspension of the identified containers is released as soon as it is determined that the corresponding node's memory usage has been reduced. The proposed method reduces the average number of container restarts by a maximum of 58% and reduces the total run time by an average of 7% and a maximum of 13% for high memory volatile workflows in Kubernetes environments.

Original languageEnglish
Title of host publicationProceedings - 2023 IEEE 20th International Conference on Mobile Ad Hoc and Smart Systems, MASS 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages606-607
Number of pages2
ISBN (Electronic)9798350324334
DOIs
Publication statusPublished - 2023
Event20th IEEE International Conference on Mobile Ad Hoc and Smart Systems, MASS 2023 - Toronto, Canada
Duration: 2023 Sept 252023 Sept 27

Publication series

NameProceedings - 2023 IEEE 20th International Conference on Mobile Ad Hoc and Smart Systems, MASS 2023

Conference

Conference20th IEEE International Conference on Mobile Ad Hoc and Smart Systems, MASS 2023
Country/TerritoryCanada
CityToronto
Period23/9/2523/9/27

Bibliographical note

Publisher Copyright:
© 2023 IEEE.

Keywords

  • container
  • Kubernetes
  • memory oversubscription

ASJC Scopus subject areas

  • Control and Optimization
  • Modelling and Simulation
  • Instrumentation
  • Artificial Intelligence
  • Computer Networks and Communications
  • Information Systems and Management

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