Machine Learning-Enhanced Data Exchange with Azure Application Programming Interface Management
The incorporation of Machine Learning (ML) into Azure Application Programming Interface (API) Management creates an advanced platform for effective and intelligent data interchange. This method meets the increasing need for smooth, scalable, and secure API connection in contemporary corporate systems. The platform uses machine learning algorithms to provide predictive analytics, anomaly detection, and dynamic API scalability according to consumption trends. Azure API Management provides centralized oversight of APIs, enabling automated policy enforcement, versioning, and monitoring features, which are augmented by machine learning algorithms to guarantee optimized speed and contextual response. These attributes enable the system to customize user experiences, intelligently prioritize traffic, and adaptively manage resources. Augmented security protocols, encompassing danger identification and traffic pattern assessment, moreover, facilitate dependable data management. The increasing need for real-time, data-driven choices highlights the innovative integration of Azure's API functionalities with machine learning technology. This integration fosters creativity, expedites digital transformation, and enhances operational agility across diverse sectors and services reliant on substantial data interchange.
Authors
- Subramani Roychoudri
- R Monisha (ORCID: https://orcid.org/0000-0002-7126-1879)
- not provided Currie B.J.
- Karthikeyan Marappan
- Ramchandar Rao R
- Shanmugapriya Inbarajan
Institutions
- National Institute of Technology Warangal (IN)
- Saint Joseph's College (US)
- Rama University (IN)
- St. Joseph's Institute of Technology (IN)
- Division of Human Resource Management (US)
- Technical Solutions (United States) (US)
Publication Details
- Published
- 2025-06-05
- DOI
- https://doi.org/10.1109/iccsp64183.2025.11088511
- Primary Topic
- Software System Performance and Reliability
- Type
- article
- Field-Weighted Citation Impact
- 0.00