research-article

A Case for Performance-Aware Deployment of Containers

Authors:

Cristina L. Abad,

Shankaranarayanan Puzhavakath Narayanan,

Bharath Balasubramanian,

Minsung JangAuthors Info & Claims

WOC '19: Proceedings of the 5th International Workshop on Container Technologies and Container Clouds

Pages 25 - 30

https://doi.org/10.1145/3366615.3368355

Published: 09 December 2019 Publication History

Abstract

Cloud-native applications are increasingly adopting microservices architectures that support the development agility required by modern software. These applications deploy their components in containers that enable microservices to be deployed across different platforms, supporting the independent scaling of the different components. However, the operational complexity of microservices presents significant challenges in maintaining the performance of such applications, especially in clouds with performance variability and unpredictability. While virtual machine based deployment of applications has been well studied---with sophisticated orchestrators in the literature and practice---there has been little such studies on the opportunity in improving application performance using performance-aware deployment strategies for containers. In this paper, we consider both the runtime and initialization time performance of containerized applications and show that default placement strategies provided by orchestrators are often insufficient. Our experiments on multiple services show that a performance-aware approach is able to outperform the default placement strategy by up to factor of 2x and 2.21x for the 50th and 99th percentiles.

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Cited By

Olabanji DFitch TMatthew O(2023)Multi-tenancy in Cloud-native Architecture: A Systematic Mapping StudyWSEAS TRANSACTIONS ON COMPUTERS10.37394/23205.2023.22.422(25-43)Online publication date: 7-Mar-2023
https://doi.org/10.37394/23205.2023.22.4
Alwabel A(2023)A Novel Container Placement Mechanism Based on Whale Optimization Algorithm for CaaS CloudsElectronics10.3390/electronics1215336912:15(3369)Online publication date: 7-Aug-2023
https://doi.org/10.3390/electronics12153369
Ding ZWang SJiang C(2023)Kubernetes-Oriented Microservice Placement With Dynamic Resource AllocationIEEE Transactions on Cloud Computing10.1109/TCC.2022.316190011:2(1777-1793)Online publication date: 1-Apr-2023
https://doi.org/10.1109/TCC.2022.3161900
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cover image ACM Conferences

WOC '19: Proceedings of the 5th International Workshop on Container Technologies and Container Clouds

December 2019

52 pages

ISBN:9781450370332

DOI:10.1145/3366615

Copyright © 2019 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 09 December 2019

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Cited By

Olabanji DFitch TMatthew O(2023)Multi-tenancy in Cloud-native Architecture: A Systematic Mapping StudyWSEAS TRANSACTIONS ON COMPUTERS10.37394/23205.2023.22.422(25-43)Online publication date: 7-Mar-2023
https://doi.org/10.37394/23205.2023.22.4
Alwabel A(2023)A Novel Container Placement Mechanism Based on Whale Optimization Algorithm for CaaS CloudsElectronics10.3390/electronics1215336912:15(3369)Online publication date: 7-Aug-2023
https://doi.org/10.3390/electronics12153369
Ding ZWang SJiang C(2023)Kubernetes-Oriented Microservice Placement With Dynamic Resource AllocationIEEE Transactions on Cloud Computing10.1109/TCC.2022.316190011:2(1777-1793)Online publication date: 1-Apr-2023
https://doi.org/10.1109/TCC.2022.3161900
Turin GBorgarelli ADonetti SDamiani FJohnsen ETapia Tarifa S(2023)Predicting resource consumption of Kubernetes container systems using resource modelsJournal of Systems and Software10.1016/j.jss.2023.111750203:COnline publication date: 13-Jul-2023
https://dl.acm.org/doi/10.1016/j.jss.2023.111750
Yang DZhao NMa HYang J(2021)Provisioning with Fine-grained Affinity for Container-enabled Cloud-edge System2021 IEEE Intl Conf on Parallel & Distributed Processing with Applications, Big Data & Cloud Computing, Sustainable Computing & Communications, Social Computing & Networking (ISPA/BDCloud/SocialCom/SustainCom)10.1109/ISPA-BDCloud-SocialCom-SustainCom52081.2021.00225(1675-1681)Online publication date: Sep-2021
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Alnafessah AGias AWang RZhu LCasale GFilieri A(2021)Quality-Aware DevOps Research: Where Do We Stand?IEEE Access10.1109/ACCESS.2021.30648679(44476-44489)Online publication date: 2021
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Wang JLi YJiang CMa CTang LGuo S(2021)Container Performance Prediction: Challenges and SolutionsCommunications and Networking10.1007/978-3-030-67720-6_27(392-402)Online publication date: 2-Feb-2021
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Ambrosino GFioccola GCanonico RVentre G(2020)Container Mapping and its Impact on Performance in Containerized Cloud Environments2020 IEEE International Conference on Service Oriented Systems Engineering (SOSE)10.1109/SOSE49046.2020.00014(57-64)Online publication date: Aug-2020
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