High-Performance Computing (HPC) systems face a wide spectrum of I/O patterns from various sources including workflows, in-Situ data operations, or from Ad-hoc file storages. However, accurately monitoring these workloads at scale is challenging due to multiple layers’ interference on system performance metrics. The metric proxy addresses this by providing real-time insights into system states, reducing overhead and storage constraints. By utilizing a Tree-Based Overlay Network (TBON) topology, it efficiently collects metrics across nodes in HPC systems. This paper explores the conceptual foundation of the metric proxy, its architecture design, and how it can be used to improve I/O performance modelling and detection of periodic I/O workload patterns, ultimately aiding in more informed system optimization strategies.