Articles Open Access
Autonomous Enterprise DevOps Automation with AI Agents and Cloud-Native Infrastructure for Continuous Delivery
Novation Ltd, Canada
Abstract
The increasing complexity of enterprise software ecosystems has created a demand for DevOps approaches capable of delivering applications rapidly, reliably, and continuously across heterogeneous cloud-native environments. Traditional DevOps automation relies heavily on predefined pipelines, manually configured infrastructure, rule-based monitoring, and human intervention when failures occur. Although these practices improve software delivery efficiency, they remain limited in their ability to reason about changing operational conditions and autonomously resolve complex delivery problems. This research proposes an autonomous enterprise DevOps automation framework that integrates artificial intelligence agents with cloud-native infrastructure to support continuous delivery. The proposed approach employs specialized AI agents for code analysis, pipeline orchestration, infrastructure provisioning, testing, security validation, observability, incident diagnosis, and remediation. Containerized workloads, Kubernetes-based orchestration, infrastructure as code, GitOps practices, and cloud services provide the operational foundation for autonomous decision-making. The methodology adopts a design-oriented research approach combining systematic literature analysis, framework design, prototype development, and empirical evaluation. The proposed system is evaluated using delivery performance, deployment frequency, lead time, change failure rate, mean time to recovery, automation coverage, resource efficiency, security compliance, and agent decision accuracy. The research aims to demonstrate how AI-driven autonomy can transform DevOps from predefined automation toward adaptive, self-correcting, and continuously optimized enterprise software delivery
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Publication Information
| Journal | International Research Journal of Innovative Engineering |
|---|---|
| Volume | 9 |
| Number | 6 |
| Pages | 17912-17921 |
| Published | 2025-11-11 |
| Issue | Vol. 9 No. 6 (2025): International Research Journal of Innovative Engineering (IRJIE) |
References
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30. Raja, G. V. (2023). AI Driven Secure Intelligent Framework for Fraud Detection Cybersecurity and Cloud Based Enterprise Systems. International Journal of Advanced Research in Computer Science & Technology (IJARCST), 6(5), 9068-9076.
31. Meesala, L. K. (2024). AI-augmented cloud security posture management for securing enterprise AI workloads. International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 10(3), 1171-1184.
32. Macha, Y. (2022). A Review of Cloud-Based CRM Systems in Healthcare: Advances, Tools, Challenges, and Best Practices. Int. J. Curr. Eng. Technol, 12(6), 848-856.
33. Chaba, A. (2018). A platform-independent API integration architecture for scalable enterprise commerce solution. International Journal of Research Publication in Engineering, Technology and Management, 1(1), 9–13.
34. Kesarpu, S. (2025, June). Contract testing with PACT: Ensuring reliable API interactions in distributed systems. The American Journal of Engineering and Technology, 7(6), 14–23. https://doi.org/10.37547/tajet/Volume07Issue06-03
35. Sivakumer, D., & Punithavel, R. K. (2024). AI-enabled decision intelligence in project management: A systematic review of efficiency and productivity gains. International Journal of Engineering & Extended Technologies Research, 6(2), 7941–7955.
36. Vas, M. R. (2025). Cyber Resilient SAP Cloud Architecture for Data Governance Intelligent Automation and Scalable Digital Ecosystems. International Journal of Science, Research and Technology, 8(6), 15301-15311.
37. Pokala, H. K. (2021). Carbon-aware Kubernetes scheduling with sustainable GitOps and energy-efficient DevOps for green cloud computing practices. Journal of Computational Analysis and Applications, 29(6), 1497-1506.
38. Singh, I. K. (2024). DevSecOps for enterprise ontology platforms: Continuous validation, security, and compliance of semantic knowledge systems. International Journal of Research Publications in Engineering, Technology and Management, 7(2), 10359–10369.
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2. Juvvadi, R. R. (2017). From record-to-report to insight-to-action: Re-engineering the finance operating model for the cloud ERP era. International Research Journal of Innovative Engineering (IRJIE), 1(2), 371–376.
3. Kumar, A., Wadhwa, M., Kalla, D., Konduru, S. C., Nandawat, C., & Sharma, M. (2025, October). Benchmarking the Trade-Offs in Object Detection: Accuracy, Speed, and Energy Efficiency. In International Conference on Artificial Intelligence and Networking (pp. 410-422). Cham: Springer Nature Switzerland.
4. Potdar, A. (2023). Designing secure sovereign cloud architectures for enterprise data analytics and digital transformation. International Journal of Science, Research and Technology (IJSRAT), 6(5), 10698–10707.
5. Chevva, P. (2025, October). A Survey of Hierarchical Reinforcement Learning for Combinatorial Optimization in Logistics. In 2025 6th International Conference on Data Analytics for Business and Industry (ICDABI) (pp. 1-6). IEEE.
6. Gummadi, V. P. K. (2021). Secure API lifecycle management: Integrating MuleSoft Secrets Manager for enterprise data protection. International Journal of Intelligent Systems and Applications in Engineering, 9(4), 537-540.
7. Gopinathan, V. R. (2025). Revolutionizing Revenue Cycle Management in the US Healthcare System Using AI-Powered Cloud Solutions. International Journal of Computer Technology and Electronics Communication, 8(4), 11106-11118.
8. Wadhwa, R. (2023). Ensuring data consistency in enterprise systems through event driven microservices and distributed transaction management. International Journal of Computer Science and Engineering Research and Development, 6(1), 24-51.
9. Tyagi, N. (2025). AI in education: Personalized learning through intelligent tutors. International Journal of Advanced Research in Computer Science & Technology (IJARCST), 8(2), 11841-11848.
10. Prasad, A. (2025). Monitoring and analyzing latency and performance in ultra low latency environments powered by RDMA. International Journal of Applied Mathematics, 38
11. Kale, P. (2023). A Federated Learning Approach to Distributed DevOps Automation in Platform Engineering Architectures. International Journal of AI, BigData, Computational and Management Studies, 4(4), 200-208.
12. Sugumar, R. (2023, September). A Novel Approach to Diabetes Risk Assessment Using Advanced Deep Neural Networks and LSTM Networks. In 2023 International Conference on Network, Multimedia and Information Technology (NMITCON) (pp. 1-7). IEEE.
13. Challa, R. (2025). Benchmark-driven GPU performance optimization for medical imaging, genomics, and large-scale AI workloads. Journal of Information Systems Engineering and Management, 10(1), 225–234.
14. Sudhan, S. K. H. H., & Kumar, S. S. (2016). Gallant Use of Cloud by a Novel Framework of Encrypted Biometric Authentication and Multi Level Data Protection. Indian Journal of Science and Technology, 9, 44.
15. Meesala, A. (2023). Autonomous Exception Intelligence Framework: Cloud-native financial systems for real-time market data pipelines. International Journal of Future Innovative Science and Technology (IJFIST), 6(6), 11768.
16. Bhagwat, V. B. (2024). A simplified transition from EBS Payroll to Cloud Payroll: Benefits and Drawbacks. Journal of Computational Analysis and Applications, 33(6).
17. Raja, G. V. (2023). Modernizing enterprise systems using AI with machine learning and cloud computing for intelligent systems. International Journal of Future Innovative Science and Technology (IJFIST), 6(6), 11713.
18. Koganti, H., & Yijie, H. (2018, December). Searching in a Sorted Linked List. In 2018 International Conference on Information Technology (ICIT) (pp. 120-125). IEEE.
19. Devarapalli, S., Vathsavai, V. G., Katkam, V., & Kanji, R. K. (2025, July). Cloud-native llmops meets dataops: A unified framework for high-volume analytical systems. In 2025 International Conference on Computing Technologies & Data Communication (ICCTDC) (pp. 01-08). IEEE.
20. Mathew, A. (2023). Sentinel AI: An Investigation into Robust Threat Mitigation Strategies for Artificial Intelligence. Educational Research (IJMCER), 5(5), 108-111.
21. Gollapudi, R. (2022). Risk-controlled near-zero-downtime Oracle database migration using GoldenGate. International Journal of Computational and Experimental Science and Engineering, 8(3), 113–123. https://doi.org/10.22399/ijcesen.5382
22. Seetala, S. R. (2025). Architecting autonomous data platforms: Integrating AI-driven governance, metadata intelligence, and data mesh principles. International Journal of Science, Engineering and Technology, 13(1).
23. Rella, B. P. (2021). Real-time data processing for machine learning: Streaming architectures, challenges, and use cases. IRE Journals, 5(4), 230–236.
24. Anand, L. (2023). Machine Learning Enabled Enterprise Integration through Intelligent API Governance Secure Cloud Infrastructure and Automated Operations. International Journal of Research and Applied Innovations, 6(3), 5972-5979.
25. Awopejo, T. E., Adigun, P. O., & Oyekanmi, T. T. (2023). Emerging applications of artificial intelligence and machine learning in modern earthquake science. International Journal of Research Publications in Engineering, Technology and Management (IJRPETM), 6(1), 8142–8154.
26. Narapareddy, V. S. R., & Yerramilli, S. K. (2024). Devops Compliance-as-Code. Universal Library of Engineering Technology., 01 (02), 47–54.
27. Vollem, S. (2023). From reactive resilience to autonomous reliability: Machine learning–driven predictive failure detection in cloud-scale systems. International Journal of Future Innovative Science and Technology (IJFIST), 6(3), 10629.
28. Onteddu, A. R., & Ram Mohan Reddy Kundavaram, D. V. AI and Deep Learning-Based Intelligent Drug Recommendation System for Patient Health Monitoring in IoT-Enabled Healthcare. https://www.researchgate.net/profile/Rammohan-Reddy-Kundavaram/publication/400399804_AI_and_Deep_Learning-Based_Intelligent_Drug_Recommendation_System_for_Patient_Health_Monitoring_in_IoT-Enabled_Healthcare/links/6982340a7247bc6473ddc38c/AI-and-Deep-Learning-Based-Intelligent-Drug-Recommendation-System-for-Patient-Health-Monitoring-in-IoT-Enabled-Healthcare.pdf
29. Bellundagi, M. (2025). DevOps transformation in enterprise environments. International Journal of Science, Technology and Convergence, 7(7).
30. Raja, G. V. (2023). AI Driven Secure Intelligent Framework for Fraud Detection Cybersecurity and Cloud Based Enterprise Systems. International Journal of Advanced Research in Computer Science & Technology (IJARCST), 6(5), 9068-9076.
31. Meesala, L. K. (2024). AI-augmented cloud security posture management for securing enterprise AI workloads. International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 10(3), 1171-1184.
32. Macha, Y. (2022). A Review of Cloud-Based CRM Systems in Healthcare: Advances, Tools, Challenges, and Best Practices. Int. J. Curr. Eng. Technol, 12(6), 848-856.
33. Chaba, A. (2018). A platform-independent API integration architecture for scalable enterprise commerce solution. International Journal of Research Publication in Engineering, Technology and Management, 1(1), 9–13.
34. Kesarpu, S. (2025, June). Contract testing with PACT: Ensuring reliable API interactions in distributed systems. The American Journal of Engineering and Technology, 7(6), 14–23. https://doi.org/10.37547/tajet/Volume07Issue06-03
35. Sivakumer, D., & Punithavel, R. K. (2024). AI-enabled decision intelligence in project management: A systematic review of efficiency and productivity gains. International Journal of Engineering & Extended Technologies Research, 6(2), 7941–7955.
36. Vas, M. R. (2025). Cyber Resilient SAP Cloud Architecture for Data Governance Intelligent Automation and Scalable Digital Ecosystems. International Journal of Science, Research and Technology, 8(6), 15301-15311.
37. Pokala, H. K. (2021). Carbon-aware Kubernetes scheduling with sustainable GitOps and energy-efficient DevOps for green cloud computing practices. Journal of Computational Analysis and Applications, 29(6), 1497-1506.
38. Singh, I. K. (2024). DevSecOps for enterprise ontology platforms: Continuous validation, security, and compliance of semantic knowledge systems. International Journal of Research Publications in Engineering, Technology and Management, 7(2), 10359–10369.
39. Rajula, A. (2024). Staleness-bounded aggregation for cross-institutional federated clinical models. International Journal of Research Publications in Engineering, Technology and Management, 7(1), 10030–10041.
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