Using a machine learning module to perform preemptive identification and reduction of risk of failure in computational systems

Input on a plurality of attributes of a computing environment is provided to a machine learning module to produce an output value that comprises a risk score that indicates a likelihood of a potential malfunctioning occurring within the computing environment. A determination is made as to whether th...

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Hauptverfasser: Robison, Micah, Olson, James E, Gupta, Lokesh M, Ahmed, Usman, Borlick, Matthew G, Oubre, Jr., Richard P, Hopkins, Richard H
Format: Patent
Sprache:eng
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Zusammenfassung:Input on a plurality of attributes of a computing environment is provided to a machine learning module to produce an output value that comprises a risk score that indicates a likelihood of a potential malfunctioning occurring within the computing environment. A determination is made as to whether the risk score exceeds a predetermined threshold. In response to determining that the risk score exceeds a predetermined threshold, an indication is transmitted to indicate that potential malfunctioning is likely to occur within the computing environment. A modification is made to the computing environment to prevent the potential malfunctioning from occurring.