Análise de desempenho de estratégias de autoscaling vertical e horizontal: um estudo de caso com o Kubernetes

• Kewyn Akshlley UFPB
• Marcus Carvalho UFPB
• Raquel Lopes UFPB

DOI: https://doi.org/10.5753/sbrc_estendido.2022.223430

Abstract

Scalable applications may adopt horizontal or vertical autoscaling to dynamically provision resources in the cloud. To help choosing the best strategy, this work aims to compare the performance of horizontal and vertical autoscaling in Kubernetes. Through mesurement experiments using synthetic load to a web application, the horizontal was shown more efficient, reacting faster to the load variation and resulting in a lower impact on the application response time.

References

Al-Dhuraibi, Y., Paraiso, F., Djarallah, N., and Merle, P. (2017). Autonomic vertical elasticity of docker containers with elasticdocker. In 2017 IEEE 10th International Conference on Cloud Computing (CLOUD), pages 472–479.

Casalicchio, E. (2017). Autonomic orchestration of containers: Problem definition and research challenges. ACM.

Casalicchio, E. and Perciballi, V. (2017). Auto-scaling of containers: The impact of relative and absolute metrics. In 2017 IEEE 2nd International Workshops on Foundations and Applications of Self* Systems (FAS*W), pages 207–214.

Jiang, J., Lu, J., Zhang, G., and Long, G. (2013). Optimal cloud resource auto-scaling for web applications. In 2013 13th IEEE/ACM International Symposium on Cluster, Cloud, and Grid Computing, pages 58–65.

Liu, C., Shie, M., Lee, Y., Lin, Y., and Lai, K. (2014). Vertical/horizontal resource scaling mechanism for federated clouds. In 2014 International Conference on Information Science Applications (ICISA), pages 1–4.

Mao, M. and Humphrey, M. (2013). Scaling and scheduling to maximize application performance within budget constraints in cloud workflows. In Proceedings of the 2013 IEEE 27th International Symposium on Parallel and Distributed Processing, IPDPS ’13, page 67–78, USA. IEEE Computer Society.

Mao, M., Li, J., and Humphrey, M. (2010). Cloud auto-scaling with deadline and budget constraints. In 2010 11th IEEE/ACM International Conference on Grid Computing.

Menasce, D. A., Dowdy, L. W., and Almeida, V. A. F. (2004). Performance by Design: Computer Capacity Planning By Example. Prentice Hall PTR, USA.

Netto, H. V., Lung, L. C., Correia, M., Luiz, A. F., and Souza, L. M. (2017). State machine replication in containers managed by Kubernetes. Journal of Systems Architecture.

Qu, C., Calheiros, R. N., and Buyya, R. (2018). Auto-scaling web applications in clouds: A taxonomy and survey. ACM Comput. Surv., 51(4).

Sedaghat, M., Hernandez-Rodriguez, F., and Elmroth, E. (2013). A virtual machine repacking approach to the horizontal vs. vertical elasticity trade-off for cloud autoscaling. In Proceedings of the 2013 ACM Cloud and Autonomic Computing Conference, CAC ’13, New York, NY, USA. Association for Computing Machinery.

Tirmazi, M., Barker, A., Deng, N., Haque, M. E., Qin, Z. G., Hand, S., Harchol-Balter, M., and Wilkes, J. (2020). Borg: the next generation. In EuroSys’20, Heraklion, Crete.

Tosatto, A., Ruiu, P., and Attanasio, A. (2015). Container-based orchestration in cloud: State of the art and challenges. In 2015 Ninth International Conference on Complex, Intelligent, and Software Intensive Systems, pages 70–75.

Yazdanov, L. and Fetzer, C. (2012). Vertical scaling for prioritized vms provisioning. In 2012 Second International Conference on Cloud and Green Computing.