Enhancing Security and Real-Time Resilience in Microservices: Automated Self-Healing Controls for Secure gRPC over HTTP/3 with AES-256-GCM

Abstract

Microservices are essential to modern distributed systems because they allow for scalability and agility, but they also present significant security and performance issues that call for rigorous mathematical answers. In this study, a performance–security model is used to describe an integrated framework for secure gRPC communication over HTTP/3 with AES-256-GCM encryption. We derive end-to-end latency analytical expressions Ltotal = Lnet + Lenc + Lproc and demonstrate how QUIC's multiplexing and 0-RTT handshake reduce Lnet whereas hardware-accelerated AES lowers Lenc We provide an algorithmic specification for runtime anomaly detection and automatic remediation, formally characterize the threat model of the system, demonstrate its termination, and bound the remediation time complexity to O(n) with regard to the number of microservices. The model's experimental deployment on a 5-node Kubernetes cluster verifies it: with only 5% more CPU overhead, mean latency dropped by 23% and throughput increased by 20% when compared to baseline HTTP/2 + TLS 1.2. The suggested approach shows how provably safe, robust, and high-performance microservice architectures can be achieved by mathematically based design of anomaly detection, cryptographic controls, and self-healing mechanisms.