Optimizing Elastic Kubernetes Services for High Availability Applications

Authors

  • Venkata Ramana Gudelli Independent Researcher, Brambleton, VA, USA

Keywords:

Kubernetes, Elastic Kubernetes Service

Abstract

Cloud native architectures are adapted rapidly which makes the deployment highly available, resilient, and scalable applications on Kubernetes. Elastic Kubernetes Services (EKS) provides an automated managed environment that facilitates dynamic resource allocation and workload distribution. But optimization of EKS for high availability requires precise tuning of cluster configurations, node auto-scaling policies, and fault tolerance mechanisms. The purpose of this paper is to examine the key architectural components which influences the EKS performance which includes pod disruption budgets, horizontal and vertical scaling strategies, and multi-region failover techniques.

References

B. Burns, J. Beda, and K. Hightower, Kubernetes: Up & Running: Dive into the Future of Infrastructure, 2nd ed. Sebastopol, CA, USA: O’Reilly Media, 2019.

D. Merkel, "Docker: Lightweight Linux containers for consistent development and deployment," Linux Journal, vol. 2014, no. 239, pp. 1-8, Mar. 2014.

C. Boettiger, "An introduction to Docker for reproducible research," ACM SIGOPS Operating Systems Review, vol. 49, no. 1, pp. 71-79, Jan. 2015.

T. Desell, "Cloud-based parallelization and analysis of Kubernetes resource allocation algorithms," in Proceedings of the 2020 IEEE International Conference on Cloud Computing Technology and Science (CloudCom), Bangkok, Thailand, 2020, pp. 124-131.

L. A. Barroso, U. Hölzle, and P. Ranganathan, The Datacenter as a Computer: An Introduction to the Design of Warehouse-Scale Machines, 3rd ed. San Rafael, CA, USA: Morgan & Claypool, 2018.

H. Kang, H. Lee, and S. Lee, "Cloud-native application monitoring system based on Kubernetes," IEEE Access, vol. 8, pp. 223458-223470, 2020.

R. Morabito, "Virtualization on Internet of Things edge devices with container technologies: A performance evaluation," IEEE Access, vol. 5, pp. 8835-8850, 2017.

M. Coppola, M. Danelutto, and A. Neri, "High availability architectures in cloud computing: Principles and practices," in Proceedings of the 2020 IEEE International Conference on High Performance Computing & Simulation (HPCS), Barcelona, Spain, 2020, pp. 17-24.

D. Kourtesis, I. Paraskakis, and J. J. Correia, "Enabling high availability in cloud-native applications using Kubernetes operators," Journal of Cloud Computing: Advances, Systems and Applications, vol. 9, no. 1, pp. 1-15, 2020.

B. Han, V. Gopalakrishnan, L. Ji, and S. Lee, "Network function virtualization: Challenges and opportunities for innovations," IEEE Communications Magazine, vol. 53, no. 2, pp. 90-97, Feb. 2015.

P. Patel, A. Ranabahu, and A. Sheth, "Service level agreement in cloud computing: A study," IEEE Internet Computing, vol. 14, no. 4, pp. 48-55, 2010.

M. Endo, E. de Souza, and F. D. Macêdo, "Kubernetes-based multi-cloud orchestration for high availability applications," in Proceedings of the 2020 IEEE International Conference on Cloud Engineering (IC2E), Sydney, Australia, 2020, pp. 92-99.

Y. Kim and J. Kim, "Self-healing mechanisms for Kubernetes-based microservice architectures," IEEE Transactions on Network and Service Management, vol. 18, no. 2, pp. 1123-1134, Jun. 2021.

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Published

22-10-2021

How to Cite

[1]
V. Ramana Gudelli, “Optimizing Elastic Kubernetes Services for High Availability Applications”, J. Computational Intel. & Robotics, vol. 1, no. 2, pp. 64–88, Oct. 2021.

Issue

Vol. 1 No. 2 (2021): Journal of Computational Intelligence and Robotics

Section

Articles

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