Cloud-Native Software Development and Interpretability in Oracle EBS and SAP: AI-Driven Optimization with Safety-Oriented Redundancy Using Markov Decision Processes

Georgios Alexandros Papadopoulos

doi:10.15662/IJRAI.2023.0606008

Authors

Georgios Alexandros Papadopoulos Senior Software Architect, Greece Author

DOI:

https://doi.org/10.15662/IJRAI.2023.0606008

Keywords:

Cloud-Native Software Development, Oracle E-Business Suite (EBS), SAP Integration, AI-Driven Optimization, Markov Decision Processes (MDPs), Safety-Oriented Redundancy, Interpretable AI, Predictive Maintenance, Enterprise Software Resilience, Fault-Tolerant Systems

Abstract

Modern enterprise applications demand scalable, resilient, and interpretable software ecosystems capable of handling complex workflows and dynamic operational requirements. This paper presents a cloud-native software development framework for Oracle E-Business Suite (EBS) and SAP systems that leverages AI-driven optimization and Markov Decision Processes (MDPs) to enhance performance, reliability, and decision-making transparency. The framework integrates safety-oriented redundancy mechanisms to mitigate risks associated with system failures, ensuring continuous availability and fault tolerance. Through interpretable AI models, the system provides insights into automated decision-making processes, facilitating compliance, auditability, and stakeholder trust. Experimental validation demonstrates improved resource allocation, predictive maintenance, and operational efficiency across heterogeneous cloud and on-premise environments. The proposed methodology establishes a foundation for intelligent, adaptive, and resilient enterprise software ecosystems that combine cloud-native design principles with rigorous AI-driven optimization.

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