Observability comes from control theory. Rudolf Kálmán (1960) defined it: "How much can you infer about system internal state just from outputs?" In software—how much can you know about what's happening inside using only logs, metrics, and traces? But different workloads have different internal states. Containers face resource contention at cluster·node·pod layers. Lambda hits cold starts and memory limits. Business logic lives in order counts and failure rates. One instrumentation can't cover all.
Today we deep-dive workload-specific observability