AI-Driven Observability in Hybrid-Cloud SAP Ecosystems: Utilizing Machine Learning for Proactive Anomaly Detection and Self-Healing Infrastructure

Authors

  • Venugopal Rapelli

Keywords:

AIOps, Sap Observability, Anomaly Detection, Self-Healing Infrastructure, Predictive Auto Scaling

Abstract

Enterprise IT environments have undergone significant changes due to the transition from on-premisessystems to Hybrid Cloud Systems. SAP S4HANA Deployments utilize multiple cloud providers withintegration to SAP BASIS Services provided by BTP (SAP Cloud Solutions). Legacy Toolsets, such asSAP Solution Manager, rely on Static THRESHOLDS for Monitoring, triggering Alerts after business operations have already been adversely impacted through Degradation of the System

References

Anil Abraham Kuriakose, The Benefits and Challenges of AIOps in Cloud-Native Environments," Algomox, 2023. Available: https://www.algomox.com/resources/blog/aiops-for-cloud-nativesystems/

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Published

2026-01-09

How to Cite

Venugopal Rapelli. (2026). AI-Driven Observability in Hybrid-Cloud SAP Ecosystems: Utilizing Machine Learning for Proactive Anomaly Detection and Self-Healing Infrastructure. Journal of Computational Analysis and Applications (JoCAAA), 35(1), 216–227. Retrieved from https://eudoxuspress.com/index.php/pub/article/view/4662

Issue

Vol. 35 No. 1 (2026): JOCAAA

Section

Articles

License

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.