Abstract: Methods and systems for a networked storage system are provided. One method includes utilizing a training dataset for prioritizing a plurality of events associated with a networked storage system using a plurality of resources. Each event is associated with a plurality of parameters, each parameter associated with a severity level determination for each event; and each event is provided an initial priority score based on a time when each event is selected for resolution. The plurality of parameters may include an event source. The method further includes using the training dataset to identify a weight of each parameter by executing an iterative prediction algorithm; determining a priority score of a new event based on the weight of each parameter; updating the training dataset with the priority score of the new event; and adjusting a resource impacted by the new event, based on the priority score of the new event.

Abstract: Methods and systems for a networked storage system are provided. One method includes utilizing a training dataset for prioritizing a plurality of events of a networked storage system using a plurality of resources. Each event is associated with a plurality of parameters that impact a severity level determination for each event; and each event is provided an initial priority score based on a time when each event is selected for resolution. The plurality of parameters may include an event source. The method further includes using the training dataset to identify a weight of each parameter by executing an iterative prediction algorithm; determining a priority score of a new event based on the weight of each parameter; updating the training dataset using the priority score of the new event; and adjusting a resource impacted by the new event, based on the priority score.