Predictive Container Auto-Scaling for Cloud-Native Applications
- Title
- Predictive Container Auto-Scaling for Cloud-Native Applications
- Author
- 이춘화
- Keywords
- Microservices; Container; Auto-Scaling; Cloud-native Application
- Issue Date
- 2019-10
- Publisher
- IEEE
- Citation
- 2019 International Conference on Information and Communication Technology Convergence (ICTC), Page. 1-3
- Abstract
- In the past decade, cloud computing has become an essential technology in many areas such as Internet of Things, artificial intelligence, and social media. In the cloud-computing environment, the auto-scaling capability of services is important to optimize cloud operating costs and Quality of Service. Therefore, there is a need for auto-scaling technology that is able to dynamically adjust resource allocation to cloud services based on incoming workload. In this paper, we present a predictive auto-scaler for Kubernetes clusters to improve the efficiency of container auto-scaling. Being based on a predictive algorithm, our auto-scaling scheme simplifies the architecture of existing auto-scaling system for more efficient service offerings. In addition, we present experimental evaluation results of our proposed scheme.
- URI
- https://ieeexplore.ieee.org/document/8939932https://repository.hanyang.ac.kr/handle/20.500.11754/154451
- ISBN
- 978-1-7281-0893-3
- DOI
- 10.1109/ICTC46691.2019.8939932
- Appears in Collections:
- COLLEGE OF ENGINEERING[S](공과대학) > COMPUTER SCIENCE(컴퓨터소프트웨어학부) > Articles
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