Abstract: An information handling system includes a storage and a processor. The storage stores a machine learning (ML) model. The processor receives first telemetry data associated with a second information handling system, and user survey data associated with the second information handling system. Based on the first telemetry data and the user survey data, the processor trains the ML model. The processor receives second telemetry data for the second information handling system. The processor executes the ML model to determine a composite score for the second information handling system.

Abstract: A method is provided, comprising: retrieving telemetry data from a first storage device; generating a failure risk score for the first storage device, the failure risk score being generated by using a failure inference engine, the failure inference engine being arranged to execute a predictive failure model for calculating the failure risk score; and outputting the failure risk score for use in servicing the first storage device.

Abstract: A method is provided, comprising: retrieving telemetry data from a first storage device; generating a failure risk score for the first storage device, the failure risk score being generated by using a failure inference engine, the failure inference engine being arranged to execute a predictive failure model for calculating the failure risk score; and outputting the failure risk score for use in servicing the first storage device.