Architecting Future-Ready Cloud and Edge Systems: A Multi-Domain Survey of Performance Tuning, Security, and AI Integration

Abstract

The proliferation of cloud and edge computing has transformed digital infrastructure by enabling scalable, low-latency, and resource-optimized services across diverse domains. However, with increasing heterogeneity in workloads and environments, future-ready architectures demand intelligent strategies for performance tuning, robust security, and seamless AI integration. This paper presents a multi-domain survey that synthesizes the latest advancements in cloud and edge system design, with a focus on three critical pillars: (1) performance optimization through automated orchestration and microservice tuning; (2) security frameworks leveraging Zero Trust, federated identity, and secure access at the edge; and (3) AI integration for predictive resource allocation, anomaly detection, and decentralized learning. Drawing from case studies in healthcare, finance, smart manufacturing, and IoT ecosystems, the paper identifies architectural patterns, key challenges, and emerging solutions that define resilient, adaptive, and intelligent cloud-edge frameworks. The findings suggest that a unified design approach—incorporating performance-aware infrastructure, embedded security, and AI-native capabilities—is essential to future-proof cloud and edge computing systems.