AI-Powered Load Prediction for Ultra-Scalable High Performance APIs
DOI:
https://doi.org/10.64180/Keywords:
AI Load Prediction, High-Performance APIs, Predictive Autoscaling, Cloud-Native Architectures, API Traffic Forecasting, Machine Learning in Infrastructure, Intelligent API Gateways, Distributed Systems OptimizationAbstract
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.
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This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
