Towards Adaptive API Traffic Management: A Systematic Architecture for High Availability and Performance

Abstract

As modern applications increasingly rely on distributed microservices, managing API traffic has become central to ensuring system reliability and responsiveness. High volumes of client requests, coupled with variable network conditions and fluctuating backend load, challenge the scalability and resilience of traditional API gateways. This paper presents a systematic architecture for adaptive API traffic management, integrating intelligent load balancing, request prioritization, and real-time feedback control to optimize performance and availability. We design a layered framework that dynamically adjusts routing decisions based on service health, response latency, and resource utilization. Through simulation and real-world deployment scenarios, our approach demonstrates significant improvements in throughput, failure recovery, and response time consistency when compared to static policies. The proposed architecture offers a scalable and resilient foundation for cloud-native systems in high-demand environments