Modern computing systems expose countless metrics, but numbers alone do not guarantee understanding. As engineers and researchers rely on dashboards to reason about performance and capacity, it becomes critical to distinguish meaningful signals from misleading measurements.
Using practical examples from CPU, memory, storage, and scheduling systems, the talk shows how metrics are collected, visualized, and interpreted in real environments. It defines what metrics are and what they are not while highlighting common pitfalls.