Sacred Heart University, USA.
World Journal of Advanced Research and Reviews, 2025, 26(01), 2758-2764
Article DOI: 10.30574/wjarr.2025.26.1.1353
Received on 14 March 2025; revised on 19 April 2025; accepted on 21 April 2025
The integration of artificial intelligence into API management marks a transformative advancement in cloud computing infrastructure. As organizations increasingly adopt microservices architectures, traditional static API management approaches prove insufficient to handle the exponential growth in traffic volume and complexity. This paradigm shift introduces intelligent automation across critical dimensions of API operations, including traffic routing, resource allocation, and security monitoring. By establishing dynamic behavioral baselines and employing predictive analytics, these AI-powered systems can anticipate demand fluctuations, optimize resource distribution, and identify emerging security threats with unprecedented accuracy. The transition from reactive to proactive management enables organizations to avoid performance degradation during peak periods while simultaneously reducing infrastructure costs through precise resource allocation. The continuous learning capabilities inherent in these systems ensure ongoing improvement without manual intervention, effectively addressing the complexity challenges introduced by microservices proliferation. This fundamental advancement promises to reshape enterprise digital service delivery, unlocking significant value through enhanced performance, efficiency, and reliability in cloud environments.
API Management; Artificial Intelligence; Predictive Scaling; Anomaly Detection; Cloud Optimization
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Prasanna Kumar Natta. AI-Powered API Management: Intelligent traffic routing and adaptive scaling. World Journal of Advanced Research and Reviews, 2025, 26(01), 2758-2764. Article DOI: https://doi.org/10.30574/wjarr.2025.26.1.1353.
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