Thermodynamics of Computational Stability — Detecting Structural Fatigue and Temporal Entropy in Runtime Systems This work introduces a conceptual framework for understanding computational infrastructures through the lens of thermodynamics and complex systems science. Traditional monitoring approaches focus on instantaneous operational metrics such as CPU usage, memory consumption, and network activity. While these indicators describe the observable state of a system, they often fail to capture the deeper structural conditions that precede instability. This paper proposes that modern runtime environments behave as non-equilibrium dynamical systems that accumulate structural entropy over time as concurrent processes interact and compete for shared resources. Drawing conceptual connections with thermodynamics, information theory, and nonlinear systems science, the study suggests that computational infrastructures exhibit phenomena analogous to structural fatigue observed in physical systems. The framework introduces the idea that runtime systems operate within a dynamic stability field where internal structural stress may accumulate long before operational degradation becomes visible. Empirical observations presented in this work indicate that structural signals of instability can emerge significantly earlier than traditional monitoring indicators, revealing patterns of temporal convergence toward instability. Rather than treating computational failures as abrupt events, this perspective interprets them as the outcome of gradual structural transitions within complex runtime environments. The study outlines the foundations of what may be described as Computational Stability Thermodynamics, a conceptual approach that integrates principles from thermodynamics, information theory, and complex systems dynamics to better understand how large-scale computational infrastructures evolve under load. By shifting the focus from instantaneous metrics to structural dynamics over time, this framework opens new possibilities for early detection of instability, predictive infrastructure diagnostics, and improved resilience in complex computational environments. The work represents the first conceptual step in a broader research direction exploring entropy dynamics, structural stability landscapes, and nonlinear behavior in computational systems.
Rafael Felippe VOIGT (Thu,) studied this question.