Apparatus and method with system error prediction

A processor-implemented method, comprising:

• generating a plurality of updated log data pieces by eliminating redundant log data pieces from a plurality of log data pieces;
• generating a plurality of log data sequences by grouping the plurality of updated log data pieces according to a predetermined number of log data pieces;
• and
• generating a trained error prediction neural network through training by labeling a plurality of system errors with different error lead times in the plurality of log data sequences;
• and
• wherein the trained error prediction neural network comprises a multi-label deep neural network (DNN) configured to output, from a single log data sequence, information of the plurality of system errors predicted to occur at a plurality of different timepoints, thereby prediction of multiple systems errors from the single log data sequence during utilization of the error prediction neural network is enabled.

A computing system, comprising:

• a processor configured to execute instructions, and
• a memory storing the instructions, which when executed by the processor configure the processor to:
• generate a plurality of log data sequences, comprising:
• generating a plurality of updated log data pieces by eliminating redundant log data pieces comprising repeated log data pieces and stopwords from a plurality of log data pieces;
• and
• generating the plurality of log data sequences by grouping the updated log data pieces according to a predetermined number of log data pieces;
• and
• generate system error prediction data using an error prediction neural network provided one log data sequence of the plurality of log data sequences;
• and
• control a system based on the generated system error prediction data,
• wherein a size of the system error prediction data changes according to a size of a log data sequence so that a number of predictable system errors changes as the size of the log data sequence changes, thereby enabling scalable error prediction adapted to system monitoring requirements,, and
• wherein the error prediction neural network configured to output, from the one log data sequence, the system error prediction data for a plurality of system errors occurring at a plurality of different timepoints, where prediction of multiple systems errors from a single log data sequence during utilization of the error prediction neural network is enabled,
• wherein the number of errors included in the system error prediction data changes according to an increase and a decrease of the number of log data pieces included in a log data sequence.