Abstract: A system and method for managing large numbers of computing devices such as cryptocurrency miners in a data center are disclosed. Status values from the computing devices are read and stored into a database, and a Gini coefficient is calculated on a subset of the stored status values. Coefficients beyond a predetermined threshold cause a support ticket to be generated if a support ticket has not already been generated and if the coefficients are not otherwise non-indicative of actual or likely computing device failures.

Abstract: Systems and methods for reporting health status for a plurality of computing devices such as within a data center are disclosed. A management device connected to the computing devices via a network executes a management application that periodically requests and receives status data from the computing devices. A pool checker may be used to track corresponding pool status data, and an environment checker may periodically request and receive environmental data from environmental sensors for temperature, humidity, and audio. A report generator creates health reports and assigns device health classifications based on the device status data, the environmental data, and the pool health data. The data may be associated with one or more locations and customers, permitting filtering of the report.

Abstract: A management device for managing a plurality of computing devices in a data center may comprise a network interface, a first module that periodically sends health status queries to the computing devices via the network interface, a second module configured to receive responses to the health status queries and collect and store health status data for the computing devices, a third module configured to create support tickets, and/or a fourth module configured to (i) create and periodically update a Cox proportional hazards (CPH) model based on the health status data; (ii) apply a deep neural network (DNN) to the input of the CPH model; (iii) determine a probability of failure for each computing device; (iv) compare each probability of failure with a threshold; and (v) cause the third module to generate a pre-failure support ticket for each computing device having determined probabilities of failure above the threshold.

Abstract: Systems and methods for reporting health status for a plurality of computing devices such as within a data center are disclosed. A management device connected to the computing devices via a network executes a management application that periodically requests and receives status data from the computing devices. A pool checker may be used to track corresponding pool status data, and an environment checker may periodically request and receive environmental data from environmental sensors for temperature, humidity, and audio. A report generator creates health reports and assigns device health classifications based on the device status data, the environmental data, and the pool health data. The data may be associated with one or more locations and customers, permitting filtering of the report.

Abstract: A management device for managing a plurality of computing devices in a data center may comprise a network interface, a first module that periodically sends health status queries to the computing devices via the network interface, a second module configured to receive responses to the health status queries and collect and store health status data for the computing devices, a third module configured to create support tickets, and/or a fourth module configured to (i) create and periodically update a Cox proportional hazards (CPH) model based on the health status data; (ii) apply a deep neural network (DNN) to the input of the CPH model; (iii) determine a probability of failure for each computing device; (iv) compare each probability of failure with a threshold; and (v) cause the third module to generate a pre-failure support ticket for each computing device having determined probabilities of failure above the threshold.

Abstract: A system and method for managing large numbers of computing devices such as cryptocurrency miners in a data center are disclosed. Status values from the computing devices are read and stored into a database, and a Gini coefficient is calculated on a subset of the stored status values. Coefficients beyond a predetermined threshold cause a support ticket to be generated if a support ticket has not already been generated and if the coefficients are not otherwise non-indicative of actual or likely computing device failures.

Abstract: A system and method for automating management and repair of a plurality of computing devices located in a data center is disclosed. Health status queries are issued for one or more of the computing devices. If responses not indicative of good device health are received, one or more repair instructions are automatically sent to the unhealthy computing device to repair the computing device by moving it to an acceptable state. If the repair instructions are not successful, a support ticket is automatically generated for the corresponding computing device or devices. Problematic statuses across areas of the data center may be detected and ticketed in addition to individual problematic devices. So-called repeat offender devices may be detected and ticketed even if the repair instructions are successful.