AI-Powered Real-Time Cloud DevOps Framework for Scalable Enterprise Operations andCybersecurity Threat Detection using SAP HANA and ERP Systems
DOI:
https://doi.org/10.15680/IJCTECE.2023.0601005Keywords:
AI-powered DevOps, Real-time cloud architecture, SAP HANA, ERP systems, Enterprise operations, Cybersecurity threat detection, Machine learning, Deep learning, DevSecOps, Real-time analytics, Cloud security, Predictive analytics, Enterprise scalability, Anomaly detection, Intelligent automationAbstract
Enterprises increasingly rely on cloud-based infrastructures and ERP ecosystems to support high-volume operations, real-time analytics, and secure digital workflows. However, rapid system scaling, complex DevOps pipelines, and evolving cyber threats pose significant challenges to operational resilience and security. This paper introduces an AI-powered real-time Cloud DevOps framework that integrates SAP HANA’s in-memory computing capabilities with ERP-aligned automation to enhance enterprise performance and security posture. The proposed architecture employs machine learning and deep learning models to enable predictive analytics, intelligent resource orchestration, and behavior-based threat detection across cloud and ERP environments. Real-time monitoring pipelines automate anomaly detection, vulnerability assessment, and continuous compliance enforcement, ensuring security is embedded throughout the DevOps lifecycle. The framework also incorporates scalable microservices, containerized deployments, and data-driven optimization strategies to improve system reliability, agility, and operational efficiency. By unifying AI-driven analytics, SAP HANA processing, and DevSecOps principles, this solution provides a robust, scalable, and adaptive foundation for modern enterprise operations facing dynamic cybersecurity risks.References
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