This work proposes an ontological re-interpretation of observability in IT systems.Rather than treating observability as the passive availability of metrics, dashboards, and alerts, the paper argues that observability functions as an integral component of an operational control system. By explicitly modeling the feedback loop between system behavior, metric computation, visualization, and human decision-making, the work demonstrates that modern observability tooling implicitly implements a human-in-the-loop control loop. Within this framework, dashboards act as control interfaces, compute layers act as controllers, and human operators act as actuators. The paper introduces a formal model for deriving a composite control variable, termed operational pressure, from heterogeneous operational metrics. The model employs normalization and temporal operators to capture instantaneous effects, accumulated stress, and accelerating degradation, yielding a bounded and interpretable signal suitable for decision support. A control-theoretic interpretation is developed using discrete-time systems, transfer-function reasoning, and PID-like temporal decomposition, applied as guiding principles rather than strict analytical assumptions. The work distinguishes monitoring-oriented systems from control-oriented systems along fundamental conceptual dimensions, including temporal semantics, feedback interpretation, and stability considerations. This paper establishes a theoretical foundation for treating observability as a component of operational control and provides a basis for future work on automated decision systems and control-oriented IT management architectures.
Alexey A. Nekludoff (Fri,) studied this question.