Authors : Shankar Dheeraj Konidena

Volume/Issue : Volume 9 - 2024, Issue 5 - May

Google Scholar : https://tinyurl.com/mr3w4hc6

Scribd : https://tinyurl.com/c2dvhah6

DOI : https://doi.org/10.38124/ijisrt/IJISRT24MAY2361

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.

Abstract : Over the past few years, the paradigm shift towards cloud computing has transformed and revolutionized how organizations manage high- performance workloads. The microservices architecture, renowned for its modularity and scalability, is increasingly being adopted to run these workloads in cloud environments. However, this transition is not without its challenges, particularly in security. This research article delves into the methods for securely running high-performance workloads as microservices in cloud environments, presenting the advantages and the challenges involved. The study aims to develop a comprehensive framework that not only addresses these security concerns but also optimizes performance, a crucial aspect in today's digital landscape. This research is a testament to our commitment to thoroughness and precision, as it combines both qualitative and quantitative approaches. Qualitative data were meticulously gathered through interviews with 15 cloud security experts, providing invaluable insights into prevalent security practices and challenges. Quantitative data, on the other hand, were collected from performance benchmarks that rigorously compared traditional monolithic applications with microservices- based applications in a cloud setting. The study employs robust statistical analysis tools such as SPSS and Grafana to analyze the collected data, ensuring the validity and reliability of our findings. Key interview findings highlighted critical security measures necessary for microservices, including service authentication, data encryption, and vulnerability management. The performance benchmarks revealed that microservices- based applications significantly outperformed monolithic applications, with notable improvements in CPU utilization, memory usage, and response time. For instance, the microservices architecture demonstrated a 21% reduction in CPU utilization and a 12% decrease in memory usage compared to its monolithic counterpart. The proposed framework integrates robust security practices, ensuring secure authentication, encrypted data transmission, and regular updates to mitigate vulnerabilities. This framework enhances security and optimizes resource allocation, leading to improved performance metrics.

Keywords : Cloud Computing, Microservices, Workloads, Cloud Security, Applications.

References :

1. Burns, B., Grant, B., Oppenheimer, D., Brewer, E., & Wilkes, J. (2016). Borg, Omega, and Kubernetes. Communications of the ACM, 59(5), 50-57.
2. Fowler, M., & Lewis, J. (2014). Microservices: a definition of this new architectural term. martinfowler.com.   Retrieved from https://martinfowler.com/articles/microservices.html
3. Jansen, W., & Grance, T. (2011). Guidelines on Security and Privacy in Public Cloud Computing. NIST Special Publication 800-144.
4. Newman, S. (2015). Building Microservices: Designing Fine-Grained Systems. O'Reilly Media.
5. NIST. (2011). The NIST Definition of Cloud Computing. National Institute of Standards and Technology.
6. Armbrust, M., Fox, A., Griffith, R., Joseph, A. D., Katz, R., Konwinski, A., ... & Zaharia, M. (2010). A view of cloud computing. Communications of the ACM, 53(4), 50-58.
7. Joshi, S., & Sharma, A. (2016). Security and privacy issues in cloud computing: a survey. International Journal of Computer Applications, 135(9), 20-25.
8. Bernstein, D., & Vij, D. (2010). Using cloud computing to create an elastic services grid. Cloud Computing, 107-129. Springer, London.
9. Haselmann, T., & Vossen, G. (2011). Migrating legacy systems to the cloud. Information Systems and e-Business Management, 9(2), 107-134.
10. Chappell, D. (2018). Microservices in Azure. Microsoft Azure.
11. Pahl, C., & Jamshidi, P. (2016). Microservices: A systematic mapping study. Proceedings of the 6th International Conference on Cloud Computing and Services Science (CLOSER), 137-146.
12. Balalaie, A., Heydarnoori, A., & Jamshidi, P. (2016). Microservices architecture enables DevOps: Migration to a cloud-native architecture. IEEE Software, 33(3), 42-52.
13. Gannon, D., Barga, R., & Sundaresan, N. (2017). Cloud-native applications. IEEE Cloud Computing, 4(5), 16-21.
14. Zhang, Q., Cheng, L., & Boutaba, R. (2010). Cloud computing: state-of-the-art and research challenges. Journal of Internet Services and Applications, 1(1), 7-18.
15. Ghahramani, S., Zhou, M., & Hon, C. (2017). Toward cloud computing QoS architecture: Analysis of cloud systems and cloud services. IEEE Communications Magazine, 55(9), 44-50.