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Microservices Security Management within Docker Containers for during the Digitization of Legacy Applications

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Abstract

Container virtualization technology facilitates the creation of microservices-based systems through continuous integration. Container-based apps can be deployed more easily when they use orchestration systems like Kubernetes, which has become the de facto standard. It can be difficult to create effective and precise orchestration systems, nevertheless. The scheduler, a crucial orchestrator task that allocates physical resources to containers, is the subject of this article. Scheduling strategies are developed using several Quality-of-Service metrics.

The CI in CI/CD stands for continuous integration. Continuous integration drives the automation in the development and delivery of the code and developers frequently apply code changes. It’s an automated process that allows multiple developers to contribute software components to the same project without integration conflicts. CI also triggers the process of testing the applications automatically upon code commit into the repository. Container virtualization technology facilitates the creation of microservices-based systems through continuous integration. Container-based apps can be deployed more easily when they use orchestration systems like Kubernetes, which has become the de facto standard. It can be difficult to create effective and precise orchestration systems, nevertheless. The scheduler, a crucial orchestrator task that allocates physical resources to containers, is the subject of this article. Scheduling strategies are developed using several Quality of Service metrics.

Keywords

Microservice, Cloud Migration, Containerization Distributed Systems, Microservice Security

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References

  1. Hou Q., Ma Y., Chen J., and Xu Y., “An Empirical Study on Inter-Commit Times in SVN,” Int. Conf. on Software Eng. and Knowledge Eng.,” pp. 132–137, 2014.
  2. O. Arafat, and D. Riehle, “The Commit Size Distribution of Open Source Software,” Proc. the 42nd Hawaii Int’l Conf. Syst. Sci. (HICSS’09), USA, pp. 1-8, 2009.
  3. C. Kolassa, D. Riehle, and M. Salim, “A Model of the Commit Size Distribution of Open Source,” Proc. the 39th Int’l Conf. Current Trends in Theory and Practice of Comput. Sci. (SOFSEM’13), Czech Republic, pp. 52–66, 2013.
  4. L. Hattori and M. Lanza, “On the nature of commits,” Proc. the 4th Int’l ERCIM Wksp. Softw. Evol. and Evolvability (EVOL’08), Italy, pp. 63–71, 2008.
  5. P. Hofmann, and D. Riehle, “Estimating Commit Sizes Efficiently,” Proc. the 5th IFIP WG 2.13 Int’l Conf. Open Source Systems (OSS’09), Sweden, pp. 105–115, 2009.
  6. Kolassa C., Riehle, D., and Salim M., “A Model of the Commit Size Distribution of Open Source,” Proceedings of the 39th International Conference on Current Trends in Theory and Practice of Computer Science (SOFSEM’13), Springer-Verlag, Heidelberg, Baden-Württemberg, p. 5266, Jan. 26-31, 2013.
  7. Arafat O., and Riehle D., “The Commit Size Distribution of Open Source Software,” Proceedings of the 42nd Hawaii International Conference on Systems Science (HICSS’09),” IEEE Computer Society Press, New York, NY, pp. 1-8, Jan. 5-8, 2009.
  8. R. Purushothaman, and D.E. Perry, “Toward Understanding the Rhetoric of Small Source Code Changes,” IEEE Transactions on Software Engineering, vol. 31, no. 6, pp. 511–526, 2005.
  9. A. Singh, V. Singh, A. Aggarwal and S. Aggarwal, "Improving Business deliveries using Continuous Integration and Continuous Delivery using Jenkins and an Advanced Version control system for Microservices-based system," 2022 5th International Conference on Multimedia, Signal Processing and Communication Technologies (IMPACT), Aligarh, India, 2022, pp. 1-4, doi: 10.1109/IMPACT55510.2022.10029149.
  10. A. Alali, H. Kagdi, and J. Maletic, “What’s a Typical Commit? A Characterization of Open Source Software Repositories,” Proc. the 16th IEEE Int’l Conf. Program Comprehension (ICPC’08), Netherlands, pp. 182-191, 2008.
  11. A. Hindle, D. Germán, and R. Holt, “What do large commits tell us?: a taxonomical study of large commits,” Proc. the 5th Int’l Working Conf. Mining Softw. Repos. (MSR’08), Germany, pp. 99-108, 2008.
  12. V. Singh, M. Alshehri, A. Aggarwal, O. Alfarraj, P. Sharma et al., "A holistic, proactive and novel approach for pre, during and post migration validation from subversion to git," Computers, Materials & Continua, vol. 66, no.3, pp. 2359–2371, 2021.
  13. Vinay Singh, Alok Aggarwal, Narendra Kumar, A. K. Saini, “A Novel Approach for Pre-Validation, Auto Resiliency & Alert Notification for SVN To Git Migration Using Iot Devices,” PalArch’s Journal of Arch. of Egypt/Egyptology, vol. 17 no. 9, pp. 7131 – 7145, 2020.
  14. Vinay Singh, Alok Aggarwal, Adarsh Kumar, and Shailendra Sanwal, “The Transition from Centralized (Subversion) VCS to Decentralized (Git) VCS: A Holistic Approach,” Journal of Electrical and Electronics Engineering, ISSN: 0974-1704, vol. 12, no. 1, pp. 7-15, 2019.
  15. Ma Y., Wu Y., and Xu Y., “Dynamics of Open-Source Software Developer’s Commit Behavior: An Empirical Investigation of Subversion,” Proceedings of the 29th Annual ACM Symposium on Applied Computing (SAC’14), pp. 1171-1173, doi: 10.1145/2554850.2555079, 2014.
  16. M. Luczak-R¨osch, G. Coskun, A. Paschke, M. Rothe, and R. Tolksdorf, “Svont-version control of owl ontologies on the concept level.” GI Jahrestagung (2), vol. 176, pp. 79–84, 2010.
  17. E. Jim´enez-Ruiz, B. C. Grau, I. Horrocks, and R. B. Llavori, “Contentcvs: A cvs-based collaborative ontology engineering tool.” in SWAT4LS. Citeseer, 2009.
  18. I. Zaikin and A. Tuzovsky, “Owl2vcs: Tools for distributed ontology development.” in OWLED. Citeseer, 2013.