Distributed Cloud Computing Infrastructure Management

Cloud computing has emerged as a foundational paradigm for delivering on-demand computing, storage, and networking services at the global scale. Since its rise in the early 2010s, major providers such as AWS and Azure have come to rely on sprawling infrastructures—hundreds of data centers housing millions of devices—to meet ever-growing customer demands. Ensuring high availability, reliability, and security across such heterogeneous and geographically dispersed hardware presents significant operational challenges, including device provisioning, real-time monitoring, predictive maintenance, and end-of-life decommissioning. In this paper, we present a comprehensive framework for distributed cloud infrastructure management that spans the full hardware and software lifecycle. We first delineate a multi-layered architecture—from data center to cluster, slice, and individual device—and describe standardized instrumentation via BMC agents, SNMP/Redfish interfaces, and proxy daemons. Building on this foundation, we detail automated workflows for zero-touch provisioning, continuous telemetry ingestion, anomaly detection, and self-healing remediation using Infrastructure-as-Code, configuration management, and runbook-driven automation. Finally, we address end-to-end lifecycle concerns by integrating predictive analytics for capacity planning, risk-based hardware retirement, and secure decommissioning. Through real-world case studies from hyperscale environments, we demonstrate how our approach reduces mean-time-to-repair, optimizes resource utilization, and enforces compliance—thereby enabling cloud providers to scale efficiently while maintaining high reliability at minimal operational cost.