Kubernetes的资源管理

E. Kim, Kyungwoon Lee, C. Yoo
{"title":"Kubernetes的资源管理","authors":"E. Kim, Kyungwoon Lee, C. Yoo","doi":"10.1109/ICOIN50884.2021.9333977","DOIUrl":null,"url":null,"abstract":"Kubernetes is the most popular container orchestration platform that enables users to create and run multiple containers in cloud environments. Kubernetes offers resource management to isolate the resource usage of containers on a host server because performance isolation is an important factor in terms of service quality. This paper investigates whether the resource management of Kubernetes is sufficient to isolate the performance of containers. This is different from previous studies that mostly focuses on efficient resource management rather than the study on performance interference. We evaluate the performance interference 1) between CPU-intensive and networkintensive containers, and 2) between multiple network-intensive containers. Our evaluation results show that containers experience performance degradation by 50% due to the co-located containers even under the resource management of Kubernetes. This paper also points out that the root cause of the performance interference between multiple network-intensive containers is CPU contention, not network bandwidth. As a result, Kubernetes needs to consider the CPU usage of network-related workloads in resource management in order to mitigate the performance interference.","PeriodicalId":6741,"journal":{"name":"2021 International Conference on Information Networking (ICOIN)","volume":"4 1","pages":"154-158"},"PeriodicalIF":0.0000,"publicationDate":"2021-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":"{\"title\":\"On the Resource Management of Kubernetes\",\"authors\":\"E. Kim, Kyungwoon Lee, C. Yoo\",\"doi\":\"10.1109/ICOIN50884.2021.9333977\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Kubernetes is the most popular container orchestration platform that enables users to create and run multiple containers in cloud environments. Kubernetes offers resource management to isolate the resource usage of containers on a host server because performance isolation is an important factor in terms of service quality. This paper investigates whether the resource management of Kubernetes is sufficient to isolate the performance of containers. This is different from previous studies that mostly focuses on efficient resource management rather than the study on performance interference. We evaluate the performance interference 1) between CPU-intensive and networkintensive containers, and 2) between multiple network-intensive containers. Our evaluation results show that containers experience performance degradation by 50% due to the co-located containers even under the resource management of Kubernetes. This paper also points out that the root cause of the performance interference between multiple network-intensive containers is CPU contention, not network bandwidth. As a result, Kubernetes needs to consider the CPU usage of network-related workloads in resource management in order to mitigate the performance interference.\",\"PeriodicalId\":6741,\"journal\":{\"name\":\"2021 International Conference on Information Networking (ICOIN)\",\"volume\":\"4 1\",\"pages\":\"154-158\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-01-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"10\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 International Conference on Information Networking (ICOIN)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICOIN50884.2021.9333977\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 International Conference on Information Networking (ICOIN)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICOIN50884.2021.9333977","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 10

摘要

Kubernetes是最流行的容器编排平台,它使用户能够在云环境中创建和运行多个容器。Kubernetes提供资源管理来隔离主机服务器上容器的资源使用情况,因为性能隔离是影响服务质量的一个重要因素。本文研究Kubernetes的资源管理是否足以隔离容器的性能。这与以往的研究主要关注有效的资源管理,而不是对绩效干扰的研究不同。我们评估了1)cpu密集型容器和网络密集型容器之间的性能干扰,以及2)多个网络密集型容器之间的性能干扰。我们的评估结果表明,即使在Kubernetes的资源管理下,容器也会由于共存的容器而导致性能下降50%。本文还指出,多个网络密集型容器之间性能干扰的根本原因是CPU争用,而不是网络带宽。因此,Kubernetes需要在资源管理中考虑与网络相关的工作负载的CPU使用情况,以减轻性能干扰。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
On the Resource Management of Kubernetes
Kubernetes is the most popular container orchestration platform that enables users to create and run multiple containers in cloud environments. Kubernetes offers resource management to isolate the resource usage of containers on a host server because performance isolation is an important factor in terms of service quality. This paper investigates whether the resource management of Kubernetes is sufficient to isolate the performance of containers. This is different from previous studies that mostly focuses on efficient resource management rather than the study on performance interference. We evaluate the performance interference 1) between CPU-intensive and networkintensive containers, and 2) between multiple network-intensive containers. Our evaluation results show that containers experience performance degradation by 50% due to the co-located containers even under the resource management of Kubernetes. This paper also points out that the root cause of the performance interference between multiple network-intensive containers is CPU contention, not network bandwidth. As a result, Kubernetes needs to consider the CPU usage of network-related workloads in resource management in order to mitigate the performance interference.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信