Support action based self learning and analytics for datacenter device hardware/firmare fault management

Techniques for support activity based self learning and analytics for datacenter device hardware/firmware fault management are described. In one example, a service event including a unique service event ID, a set of prioritized cause and support engineer actions/recommendations and associated unique...

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Bibliographische Detailangaben
Hauptverfasser: Shivanna, Suhas, Polackal, Bino Joseph, Ahmed, Afreen
Format: Patent
Sprache:eng
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Zusammenfassung:Techniques for support activity based self learning and analytics for datacenter device hardware/firmware fault management are described. In one example, a service event including a unique service event ID, a set of prioritized cause and support engineer actions/recommendations and associated unique support engineer action codes are generated for the support engineer upon detecting a hardware/firmware failure event. Support engineer actions taken by the support engineer upon completing the service event are then received. The support engineer actions are then analyzed using the set of prioritized cause and support engineer actions/recommendations and FRU configuration information before and after servicing the hardware/firmware failure. Any potential errors resulting from the support engineer actions are then determined and notified at real-time to the support engineer based on the outcome of the analysis. Any needed updates to the set of prioritized cause and support engineer actions/recommendations are then recommended.