Research Article
Container Performance Prediction: Challenges and Solutions
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@INPROCEEDINGS{10.1007/978-3-030-67720-6_27, author={Jiwei Wang and Yuegang Li and Congfeng Jiang and Chao Ma and Linlin Tang and Shuangshuang Guo}, title={Container Performance Prediction: Challenges and Solutions}, proceedings={Communications and Networking. 15th EAI International Conference, ChinaCom 2020, Shanghai, China, November 20-21, 2020, Proceedings}, proceedings_a={CHINACOM}, year={2021}, month={2}, keywords={Virtualization Container Containerized cloud Performance prediction Machine learning}, doi={10.1007/978-3-030-67720-6_27} }- Jiwei Wang
Yuegang Li
Congfeng Jiang
Chao Ma
Linlin Tang
Shuangshuang Guo
Year: 2021
Container Performance Prediction: Challenges and Solutions
CHINACOM
Springer
DOI: 10.1007/978-3-030-67720-6_27
Abstract
With popularity of cloud computing services, more and more tasks and services are deployed on large-scale clusters. As an emerging technology in cloud computing field, containers make virtualization extremely lightweight. However, lack of prediction causes scheduling decisions lag behind the dynamics of clouds. Thus, how to carry out performance prediction before container scaling has become an urgent problem to be resolved. Here we emphasized the necessity of container performance prediction and summarized the current research progress and effort of container performance modeling. Finally, we compared pros and cons of numerical analysis and machine learning in terms of practice.
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