Real-Time Predictive DevOps Intelligence for Risk-Aware Digital Business Processes in Cloud and SAP Ecosystems
DOI:
https://doi.org/10.15662/IJARCST.2024.0704016Keywords:
Predictive DevOps Intelligence, Real-Time Risk Management, Cloud Computing, SAP Ecosystems, Digital Business Processes, AI-Driven Analytics, CI/CD AutomationAbstract
The increasing complexity of cloud-native enterprise systems, particularly those integrating SAP platforms and digital business workflows, has introduced significant challenges in maintaining performance, reliability, and risk compliance across DevOps pipelines. Real-time digital business processes—such as online advertising platforms, customer engagement systems, and SAP-driven enterprise applications—demand continuous integration and delivery (CI/CD) pipelines that can proactively anticipate failures, performance degradation, and operational risks. This paper presents a Real-Time Predictive DevOps Intelligence framework that leverages artificial intelligence and data-driven performance forecasting to enable risk-aware automation across CI/CD pipelines in cloud and SAP ecosystems. The proposed approach continuously collects telemetry data from application logs, network metrics, infrastructure monitoring tools, and SAP workloads to train predictive models capable of forecasting pipeline bottlenecks, UI test failures, and deployment risks before they impact production systems. By integrating machine learning–based anomaly detection and performance prediction into DevOps workflows, the framework enables proactive risk mitigation, optimized release decisions, and improved service reliability. Experimental analysis demonstrates that the proposed solution significantly reduces deployment failures, improves mean time to recovery, and enhances operational visibility across hybrid cloud environments. The results highlight the effectiveness of predictive DevOps intelligence in supporting resilient, scalable, and risk-aware digital business operations within modern cloud and SAP-driven enterprises.References
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