ISSN (Print): 3078-4425 ISSN (Online): 3078-4425
International Journal of Engineering Fields Official Publication of Octopus Publication, Hong Kong
Cover of October-December 2024
research article

AI-Powered Load Prediction for Ultra-Scalable High Performance APIs

  • Ishu Anand Jaiswal
    United States

Vol. 2 , Issue 4 (2024) · pp. 46-53

Country: United States

DOI: 10.64180/ijef.242405

Abstract

Application Programming Interfaces (APIs) are essential to modern digital services because they are used to connect distributed applications, microservices, and cloud platforms. With the rising need of real-time applications globally, APIs have to be able to support the high request volumes with the low latency and high availability. Old fashioned load balancing and resource allocation schemes tend to be reactive and rely on some predetermined threshold or historical average, preventing them in very dynamic traffic conditions. Artificial Intelligence (AI) can be used to provide more opportunities in predictive infrastructure management since it allows them to foresee fluctuations in workload and proactively allocate resources.

Keywords: AI Load Prediction High-Performance APIs Predictive Autoscaling Cloud-Native Architectures API Traffic Forecasting Machine Learning in Infrastructure Intelligent API Gateways Distributed Systems Optimization
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