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The impact of directed pod eviction on Kubernetes resource utilization
Umeå University, Faculty of Science and Technology, Department of Computing Science. (Autonomous Distributed Systems Lab)ORCID iD: 0000-0003-0395-8313
Umeå University, Faculty of Science and Technology, Department of Computing Science.ORCID iD: 0000-0003-0106-3049
Umeå University, Faculty of Science and Technology, Department of Computing Science.ORCID iD: 0000-0002-2633-6798
2023 (English)In: 2023 IEEE international conference on service-oriented system engineering (SOSE): proceedings, IEEE, 2023, p. 81-90Conference paper, Published paper (Refereed)
Abstract [en]

One of the promises of container orchestration technologies is that they enable effective utilization of hardware resources and thus reduce infrastructure costs. However, as applications scale up and down over time in a Kubernetes-managed environment, the cluster may enter a state of resource fragmentation. In such a state, the cluster's hardware cannot be used to its full potential because resources become locked by poor Pod to Node mappings. This paper shows that such problems are common as workload requirements approach a cluster's resource capacity. Additionally, we present an experimental analysis of directed Pod eviction as a technique to combat the issue of resource fragmentation. Our findings show that directed Pod eviction can reduce resource fragmentation and allow clusters to run a given workload using 16.7% fewer Nodes than is consistently possible using standard Kubernetes scheduling. These findings are unaffected by applying input shaking to the experimental analysis, strengthening confidence in the generality of these resource utilization improvements.

Place, publisher, year, edition, pages
IEEE, 2023. p. 81-90
Series
IEEE International Symposium on Service-Oriented System Engineering, ISSN 2640-8228, E-ISSN 2642-6587
Keywords [en]
Cloud computing, Kubernetes, scheduling, directed Pod eviction, resource fragmentation, resource utilization, experimental evaluation, Descheduler for Kubernetes
National Category
Computer Systems Computer Sciences
Research subject
Computer Science; Computer Systems
Identifiers
URN: urn:nbn:se:umu:diva-214710DOI: 10.1109/SOSE58276.2023.00016ISI: 001084635000010Scopus ID: 2-s2.0-85174951364ISBN: 979-8-3503-2239-2 (electronic)ISBN: 979-8-3503-2240-8 (print)OAI: oai:DiVA.org:umu-214710DiVA, id: diva2:1800154
Conference
2023 IEEE International Conference on Service-Oriented System Engineering (SOSE), Athes, Greece, July 17-20, 2023
Funder
Knut and Alice Wallenberg Foundation, 2019.0352Available from: 2023-09-26 Created: 2023-09-26 Last updated: 2025-09-25Bibliographically approved

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Larsson, OliverKlein, CristianElmroth, Erik

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CiteExportLink to record
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Citation style
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