Energy efficiency in large-scale computer systems, such as cluster systems, is a significant concern today due to high energy costs and the need to reduce environmental impact. This pioneering project explores the utilization of V-nets as a transformative tool for extracting crucial insights from such event sequences through diagnostic analysis. By conducting a comprehensive investigation into V-nets’ formalism, this study focuses on constructing temporal patterns that unlock the actual energy performance capabilities of Scalable Computing Systems (SCS). Although empirical testing on specific systems is not yet available, the paramount significance of this innovative formalism becomes evident, offering numerous advantages, including the identification of simultaneous events, detection of partial event sequences, and discernment of false positives. Pushing the boundaries of knowledge and optimization in SCS within the realm of Industry 4.0, this work seamlessly bridges the gap between theoretical analysis and practical applications. It confidently asserts that the experimental success observed in smaller systems can indeed be extended with confidence to larger machines and parallel computing systems on a grand scale.