From Provisioning to Decommissioning, Innovative Automation in Containers Management

Authors

  • Sandeep Chinamanagonda Senior Software Engineer at Oracle Cloud infrastructure, USA Author
  • Vishnu Vardhan Reddy Boda Sr. Software engineer at Optum Services inc, USA Author
  • Hitesh Allam Software Engineer at Concor IT, USA Author
  • Jayaram Immaneni SRE Lead at JP Morgan Chase, USA Author
  • Anirudh Mustyala Sr. Associate Software Engineer at JP Morgan Chase, USA Author

Keywords:

Kubernetes Automation, AI-Driven Tools, Container Lifecycle Management

Abstract

Organization managements of containerized environments are being revolutionized by intelligent automations, which streamlines positions & decommissioning procedures. Although these containers are more essential for the deployment of contemporary applications, manual administration becomes more ineffective & prone to errors as workloads to get more complicated. Intelligent automations optimize the whole container lifecycle by combining Artificial Intelligence, ML & orchestration technologies. It forecasts the resource requirements during provisioning & guarantees the error-free positions. When automated systems are in use, they keep an eye on performances, adjust resources such as necessary & they take care of any problems before they produce problems. Automated inspections & the actual time threats detection improves security by guaranteeing compliances & lowering vulnerabilities. Automation effectively cleans up resources during container decommissioning, reducing wastes & improving infrastructure. This method can eliminate downtime, enhances applications performance & lessons the effort of IT workers. By using intelligent automation, businesses may be remained competitive, develops more quickly & concentrates on strategic objectives rather than the mundane duties. Intelligent automation provides the speed, effectiveness & dependability required to efficiently manages scalable, secure containerized environments as part of the huge trend of digital transformations.

References

1. Boutaba, R., Shahriar, N., Salahuddin, M. A., Chowdhury, S. R., Saha, N., & James, A. (2021, August). AI-driven Closed-loop Automation in 5G and beyond Mobile Networks. In Proceedings of the 4th FlexNets Workshop on Flexible

Networks Artificial Intelligence Supported Network Flexibility and Agility (pp. 1-6).

2. Harzenetter, L., Breitenbücher, U., Képes, K., & Leymann, F. (2020). Freezing and defrosting cloud applications: automated saving and restoring of running applications. SICS Software-Intensive Cyber-Physical Systems, 35, 101-114.

3. Popa, C. L., Carutasu, G., Cotet, C. E., Carutasu, N. L., & Dobrescu, T. (2017). Smart city platform development for an automated waste collection system. Sustainability, 9(11), 2064.

4. Chhetri, M. B., Chichin, S., Vo, Q. B., & Kowalczyk, R. (2013, June). Smart Cloud

Bench--Automated performance benchmarking of the cloud. In 2013 IEEE Sixth International Conference on Cloud Computing (pp. 414-421). IEEE.

5. Ramos, E., Morabito, R., & Kainulainen, J. P. (2019). Distributing intelligence to the edge and beyond [research frontier]. IEEE Computational Intelligence Magazine, 14(4), 65-92.

6. Keller, A. (2017). Challenges and directions in service management automation. Journal of Network and Systems Management, 25(4), 884-901.

7. Harzenetter, L., Breitenbücher, U., Binz, T., & Leymann, F. (2023). An Integrated Management System for Composed Applications Deployed by Different Deployment Automation Technologies. SN Computer Science, 4(4), 370.

8. Theodorou, V., Gerostathopoulos, I., Alshabani, I., Abelló, A., & Breitgand, D. (2021, May). MEDAL: An AI-driven data fabric concept for elastic cloud-to-edge intelligence. In International Conference on Advanced Information Networking and Applications (pp. 561-571). Cham: Springer International Publishing.

9. Ortiz, J., Sanchez-Iborra, R., Bernabe, J. B., Skarmeta, A., Benzaid, C., Taleb, T.,

... & Lopez, D. (2020, August). INSPIRE-5Gplus: Intelligent security and

pervasive trust for 5G and beyond networks. In Proceedings of the 15th International Conference on Availability, Reliability and Security (pp. 1-10).

10. Raj, P., Raman, A., Raj, P., & Raman, A. (2018). Multi-cloud management: Technologies, tools, and techniques. Software-Defined Cloud Centers: Operational and Management Technologies and Tools, 219-240.

11. Inam, R., Karapantelakis, A., Vandikas, K., Mokrushin, L., Feljan, A. V., & Fersman, E. (2015, September). Towards automated service-oriented lifecycle management for 5G networks. In 2015 IEEE 20th Conference on Emerging

Technologies & Factory Automation (ETFA) (pp. 1-8). IEEE.

12. OZKILINC, B. (2010). Measuring and allocating costs of a virtual infrastructure, automating the process of provisioning of virtual machines on VMware lifecycle manager and Vmware chargeback.

13. Li, X., Chiasserini, C. F., Mangues-Bafalluy, J., Baranda, J., Landi, G., Martini, B.,... & Valcarenghi, L. (2021). Automated service provisioning and hierarchical SLA management in 5G systems. IEEE Transactions on Network and Service Management, 18(4), 4669-4684.

14. Keller, A., & Dawson, C. (2018, April). Months into minutes: Rolling out changes

faster with service management automation. In NOMS 2018-2018 IEEE/IFIP Network Operations and Management Symposium (pp. 1-14). IEEE.

15. Chouliaras, S., & Sotiriadis, S. (2023). An adaptive auto-scaling framework for cloud resource provisioning. Future Generation Computer Systems, 148, 173-183.

16. Katari, A., & Rodwal, A. NEXT-GENERATION ETL IN FINTECH: LEVERAGING AI AND ML FOR INTELLIGENT DATA TRANSFORMATION.

17. Katari, A. Case Studies of Data Mesh Adoption in Fintech: Lessons Learned-Present Case Studies of Financial Institutions.

18. Katari, A. (2023). Security and Governance in Financial Data Lakes: Challenges and Solutions. Journal of Computational Innovation, 3(1).

19. Katari, A., & Vangala, R. Data Privacy and Compliance in Cloud Data Management for Fintech.

20. Katari, A., Ankam, M., & Shankar, R. Data Versioning and Time Travel In Delta Lake for Financial Services: Use Cases and Implementation.

21. Nookala, G., Gade, K. R., Dulam, N., & Thumburu, S. K. R. (2024). Building Cross-Organizational Data Governance Models for Collaborative Analytics. MZ Computing Journal, 5(1). 2024/3/13

22. Nookala, G. (2024). The Role of SSL/TLS in Securing API Communications: Strategies for Effective Implementation. Journal of Computing and Information Technology, 4(1). 2024/2/13

23. Nookala, G. (2024). Adaptive Data Governance Frameworks for Data-Driven Digital Transformations. Journal of Computational Innovation, 4(1). 2024/2/13

24. Nookala, G., Gade, K. R., Dulam, N., & Thumburu, S. K. R. (2023). Zero-Trust Security Frameworks: The Role of Data Encryption in Cloud Infrastructure. MZ Computing Journal, 4(1).

25. Boda, V. V. R., & Immaneni, J. (2023). Automating Security in Healthcare: What Every IT Team Needs to Know. Innovative Computer Sciences Journal, 9(1).

26. Immaneni, J. (2023). Best Practices for Merging DevOps and MLOps in Fintech. MZ Computing Journal, 4(2).

27. Immaneni, J. (2023). Scalable, Secure Cloud Migration with Kubernetes for Financial Applications. MZ Computing Journal, 4(1).

28. Boda, V. V. R., & Immaneni, J. (2022). Optimizing CI/CD in Healthcare: Tried and True Techniques. Innovative Computer Sciences Journal, 8(1).

29. Thumburu, S. K. R. (2023). Leveraging AI for Predictive Maintenance in EDI Networks: A Case Study. Innovative Engineering Sciences Journal, 3(1).

30. Thumburu, S. K. R. (2023). AI-Driven EDI Mapping: A Proof of Concept. Innovative Engineering Sciences Journal, 3(1).

31. Thumburu, S. K. R. (2023). EDI and API Integration: A Case Study in Healthcare, Retail, and Automotive. Innovative Engineering Sciences Journal, 3(1).

32. Thumburu, S. K. R. (2023). Quality Assurance Methodologies in EDI Systems Development. Innovative Computer Sciences Journal, 9(1).

33. Thumburu, S. K. R. (2023). Data Quality Challenges and Solutions in EDI Migrations. Journal of Innovative Technologies, 6(1).

34. Komandla, V. Crafting a Clear Path: Utilizing Tools and Software for Effective Roadmap Visualization.

35. Komandla, V. (2023). Safeguarding Digital Finance: Advanced Cybersecurity Strategies for Protecting Customer Data in Fintech.

36. Komandla, Vineela. "Crafting a Vision-Driven Product Roadmap: Defining Goals and Objectives for Strategic Success." Available at SSRN 4983184 (2023).

37. Komandla, Vineela. "Critical Features and Functionalities of Secure Password Vaults for Fintech: An In-Depth Analysis of Encryption Standards, Access Controls, and Integration Capabilities." Access Controls, and Integration Capabilities (January 01, 2023) (2023).

38. Komandla, Vineela. "Crafting a Clear Path: Utilizing Tools and Software for Effective Roadmap Visualization." Global Research Review in Business and Economics [GRRBE] ISSN (Online) (2023): 2454-3217.

39. Muneer Ahmed Salamkar. Real-Time Analytics: Implementing ML Algorithms to Analyze Data Streams in Real-Time. Journal of AI-Assisted Scientific Discovery, vol. 3, no. 2, Sept. 2023, pp. 587-12

40. Muneer Ahmed Salamkar. Feature Engineering: Using AI Techniques for Automated Feature Extraction and Selection in Large Datasets. Journal of Artificial Intelligence Research and Applications, vol. 3, no. 2, Dec. 2023, pp. 1130-48

41. Muneer Ahmed Salamkar. Data Visualization: AI-Enhanced Visualization Tools to Better Interpret Complex Data Patterns. Journal of Bioinformatics and Artificial Intelligence, vol. 4, no. 1, Feb. 2024, pp. 204-26

42. Muneer Ahmed Salamkar, and Jayaram Immaneni. Data Governance: AI Applications in Ensuring Compliance and Data Quality Standards. Journal of AI-Assisted Scientific Discovery, vol. 4, no. 1, May 2024, pp. 158-83

43. Naresh Dulam, et al. “Foundation Models: The New AI Paradigm for Big Data Analytics ”. Journal of AI-Assisted Scientific Discovery, vol. 3, no. 2, Oct. 2023, pp. 639-64

44. Naresh Dulam, et al. “Generative AI for Data Augmentation in Machine Learning”. Journal of AI-Assisted Scientific Discovery, vol. 3, no. 2, Sept. 2023, pp. 665-88

45. Naresh Dulam, and Karthik Allam. “Snowpark: Extending Snowflake’s Capabilities for Machine Learning”. African Journal of Artificial Intelligence and Sustainable Development, vol. 3, no. 2, Oct. 2023, pp. 484-06

46. Naresh Dulam, and Jayaram Immaneni. “Kubernetes 1.27: Enhancements for Large-Scale AI Workloads ”. Journal of Artificial Intelligence Research and Applications, vol. 3, no. 2, July 2023, pp. 1149-71

47. Naresh Dulam, et al. “GPT-4 and Beyond: The Role of Generative AI in Data Engineering”. Journal of Bioinformatics and Artificial Intelligence, vol. 4, no. 1, Feb. 2024, pp. 227-49

48. Sarbaree Mishra, and Jeevan Manda. “Building a Scalable Enterprise Scale Data Mesh With Apache Snowflake and Iceberg”. Journal of AI-Assisted Scientific Discovery, vol. 3, no. 1, June 2023, pp. 695-16

49. Sarbaree Mishra. “Scaling Rule Based Anomaly and Fraud Detection and Business Process Monitoring through Apache Flink”. Australian Journal of Machine Learning Research & Applications, vol. 3, no. 1, Mar. 2023, pp. 677-98

50. Sarbaree Mishra. “The Lifelong Learner - Designing AI Models That Continuously Learn and Adapt to New Datasets”. Journal of AI-Assisted Scientific Discovery, vol. 4, no. 1, Feb. 2024, pp. 207-2

51. Sarbaree Mishra, and Jeevan Manda. “Improving Real-Time Analytics through the Internet of Things and Data Processing at the Network Edge ”. Journal of AI-Assisted Scientific Discovery, vol. 4, no. 1, Apr. 2024, pp. 184-06

52. Sarbaree Mishra. “Cross Modal AI Model Training to Increase Scope and Build More Comprehensive and Robust Models. ”. Journal of AI-Assisted Scientific Discovery, vol. 4, no. 2, July 2024, pp. 258-80

53. Babulal Shaik. Developing Predictive Autoscaling Algorithms for Variable Traffic Patterns . Journal of Bioinformatics and Artificial Intelligence, vol. 1, no. 2, July 2021, pp. 71-90

54. Babulal Shaik, et al. Automating Zero-Downtime Deployments in Kubernetes on Amazon EKS . Journal of AI-Assisted Scientific Discovery, vol. 1, no. 2, Oct. 2021, pp. 355-77

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Published

30-10-2024

How to Cite

[1]
Sandeep Chinamanagonda, Vishnu Vardhan Reddy Boda, Hitesh Allam, Jayaram Immaneni, and Anirudh Mustyala, “From Provisioning to Decommissioning, Innovative Automation in Containers Management”, Aus. J. of Machine Learning Res. & App., vol. 4, no. 2, pp. 236–259, Oct. 2024, Accessed: Mar. 14, 2025. [Online]. Available: https://ajmlra.org/index.php/publication/article/view/105