Predictive Service Intelligence System for Immersion Cooled Computing Infrastructure

Abstract

Predictive Service Intelligence System for Immersion Cooled Computing Infrastructure Existing immersion cooling infrastructure monitoring systems assess component status using threshold values ​​based on instantaneous sensor measurements. This reactive approach leads to unplanned downtime, failure to detect incremental degradation, and the inability to perform integrated reliability assessments at the infrastructure level, as it can only generate warnings in advanced stages of deterioration. This invention presents a predictive service intelligence system that derives the service status of infrastructure components not from instantaneous threshold comparisons, but from a multidimensional combination of trends in flow rate, thermal profile, and power consumption over time.The system comprises a telemetry acquisition layer (900), a trend analysis engine (910) that derives time series trends, a health assessment layer (920) that generates a service life score or reliability indicator from a combination of trends, and a service estimation module (930) that predicts maintenance needs and service scheduling. The invention incorporates a dynamic degradation model covering immersion infrastructure-specific degradation types such as filter clogging, pump aging, and coolant performance degradation, preferably including multiple rack-level cluster reliability orchestrations and runtime model update mechanisms. The system coordinates with workload scheduling and flow orchestration systems via an infrastructure coordination interface (950).