AI-Driven Secure and Cloud-Native Microservice Architectures for High-Performance Financial and Hardware Accelerator Systems

This research describes an end-to-end architecture for financial systems that is capable of bringing together cloud-native microservice architecture with artificial intelligence and hardware accelerators. We have Kubernetes based containers and orchestrated containers using service mesh control plane technologies, real-time AI based threat mitigation using transformerbased detection models. Zero Trust security based on mutual TLS authentication and Policy based access controls based on Istio and Envoy proxies. Hardware acceleration: FPGA, GPU cluster helps for transaction processing in ultra-low latency in the sub-millisecond range. KServe Enterprise intelligence gives intelligent load balancing and predictive scaling with machine learning models. Kernel-level monitoring by eBPF integration, and network security integration of Cilium are examples of how performance improvement could be measured (latency reduction by 40 % and availability of 99.99 %) showing that the framework is suitable for mission-critical financial applications.