Cloud-Native Microservices Architectures: Performance, Security, and Cost Optimization Strategies
DOI:
https://doi.org/10.63282/3050-9246.IJETCSIT-V4I1P103Keywords:
Microservices, Kubernetes, Performance Optimization, Security, Cost Optimization, Service Mesh, Devsecops, Containerization, ScalabilityAbstract
Microservices, as a paradigm for deploying applications, have popularized many new software creation and distribution approaches. Microservice architectures are built from several loosely coupled components, are usually implemented in containers and are orchestrated and dynamically provisioned; such technologies provide clear advantages in terms of flexibility, expandability, and sustainability. However, the fact is that the implementation of microservices has certain problems, such as performance problems, security problems, and cost problems, which exist inherently in the microservices architecture. This paper aims to discuss and provide holistic approaches for improving efficiency, making the architecture more secure, and reducing the costs of microservices systems in the cloud environment. It further elaborates on each of these factors, along with the backing of scientific support and real-life experiences of cloud service providers before 2023. Microservices and cloud native characteristics: In this paper, we first briefly introduce microservices. When presenting the key technologies in the survey, the advancements in microservice technologies such as container orchestration platform, service mesh, and distributed tracing system- will be highlighted with the help of tools such as Kubernetes, istio, and jaeger, among others. Optimisation for Performance: Aspects such as load balancing, communication models involving the asynchronous model, and resource autoscaling are discussed further. Shield features focused are employments on zero-trust architecture, API gateway optimization, and container image. He develops rightsizing procedures for cost optimization and uses spot instances as well as FinOps frameworks. The results of the experiments are provided, and the real-world scenario with 30 percent cost savings and 45 percent lower latency in the e-commerce site after the optimization is presented. The paper also presents prospective studies on topics such as serverless and the role of AI in observability
Downloads
References
[1] Rodriguez, M. A., & Buyya, R. (2019). Container‐based cluster orchestration systems: A taxonomy and future directions. Software: Practice and Experience, 49(5), 698-719.
[2] Merkel, D. (2014). Docker: lightweight Linux containers for consistent development and deployment. Linux j, 239(2), 2.
[3] Burns, B., Grant, B., Oppenheimer, D., Brewer, E., & Wilkes, J. (2016). Borg, Omega, and Kubernetes. Communications of the ACM, 59(5), 50-57.
[4] Li, B., Peng, X., Xiang, Q., Wang, H., Xie, T., Sun, J., & Liu, X. (2022). Enjoy your observability: an industrial survey of microservice tracking and analysis. Empirical Software Engineering, 27, 1-28.
[5] Crawley, K. (2019). Getting started with observability lab: Opentracing, Prometheus, and jaeger.
[6] Sigelman, B. H., Barroso, L. A., Burrows, M., Stephenson, P., Plakal, M., Beaver, D., ... & Shanbhag, C. (2010). Dapper, a large-scale distributed systems tracing infrastructure.
[7] Barabanov, A., & Makrushin, D. (2020). Authentication and authorization in microservice-based systems: a survey of architecture patterns. arXiv preprint arXiv:2009.02114.
[8] Stafford, V. (2020). Zero trust architecture. NIST special publication, 800(207), 800-207.
[9] Gade, K. R. (2022). Cloud-Native Architecture: Security Challenges and Best Practices in Cloud-Native Environments. Journal of Computing and Information Technology, 2(1).
[10] Salah, T., Zemerly, M. J., Yeun, C. Y., Al-Qutayri, M., & Al-Hammadi, Y. (2016, December). The evolution of distributed systems towards a microservices architecture. In 2016 11th International Conference for Internet Technology and Secured Transactions (ICITST) (pp. 318-325). IEEE.
[11] De Lauretis, L. (2019, October). From monolithic architecture to microservices architecture. In 2019 IEEE International Symposium on Software Reliability Engineering Workshops (ISSREW) (pp. 93-96). IEEE.
[12] Bushong, V., Abdelfattah, A. S., Maruf, A. A., Das, D., Lehman, A., Jaroszewski, E., ... & Bures, M. (2021). On microservice analysis and architecture evolution: A systematic mapping study. Applied Sciences, 11(17), 7856.
[13] Odun-Ayo, I., Geteloma, V., Eweoya, I., & Ahuja, R. (2019). Virtualization, containerization, composition, and orchestration of cloud computing services. In Computational Science and Its Applications–ICCSA 2019: 19th International Conference, Saint Petersburg, Russia, July 1–4, 2019, Proceedings, Part IV 19 (pp. 403-417). Springer International Publishing.
[14] Rufino, J., Alam, M., Ferreira, J., Rehman, A., & Tsang, K. F. (2017, March). Orchestration of containerized microservices for IIoT using Docker. In 2017 IEEE International Conference on Industrial Technology (ICIT) (pp. 1532-1536). IEEE.
[15] Mateus-Coelho, N., Cruz-Cunha, M., & Ferreira, L. G. (2021). Security in microservices architectures. Procedia Computer Science, 181, 1225-1236.
[16] Dias, W. K. A. N., & Siriwardena, P. (2020). Microservices security in action. Simon and Schuster.
[17] Thota, R. C. (2023). Cost optimization strategies for microservices in AWS: Managing resource consumption and scaling efficiently. International Journal of Science and Research Archive, 10(2), 1-12.
[18] Baškarada, S., Nguyen, V., & Koronios, A. (2020). Architecting microservices: Practical opportunities and challenges. Journal of Computer Information Systems.
[19] Villamizar, M., Garcés, O., Ochoa, L., Castro, H., Salamanca, L., Verano, M., ... & Lang, M. (2017). Cost comparison of running web applications in the cloud using monolithic, microservice, and AWS Lambda architectures. Service Oriented Computing and Applications, 11, 233-247.
[20] Leitner, P., Cito, J., & Stöckli, E. (2016, December). Modelling and managing deployment costs of microservice-based cloud applications. In Proceedings of the 9th International Conference on Utility and Cloud Computing (pp. 165-174).
