Apparatus and method for monitoring computer system

A monitoring apparatus for monitoring a computer system, the monitoring apparatus comprising:

• at least one hardware processor;
• and
• a software program that is configured to, when executed by the at least one hardware processor,
• collect performance data on a plurality of performance items related to performance of the computer system,
• during a machine-learning period, use a portion of the performance data that represents degraded performance of the computer system to train a machine-learning classifier to output a pattern score that represents a similarity to at least one reference pattern of performance items associated with degradation of an evaluation index;
• after the machine-learning period, apply the machine-learning classifier to target performance data to produce one or more pattern scores for the target performance data, and determine a reference pattern that is most similar to the target performance data based on the produced one or more pattern scores, and
• output a label associated with the reference pattern that is determined to be most similar to the target performance data.

A method for monitoring a computer system, the method comprising:

• collecting performance data on a plurality of performance items related to performance of the computer system;
• accessing at least one performance degradation cause model that associates each of a plurality of cause events with degradation performance items that are degraded by the cause event;
• accessing a job execution history that comprises, for each of a plurality of jobs executed by the computer system, a type of the job and an execution period of the job, during a machine-learning period, using a portion of the performance data that represents normal behavior of the computer system to train a machine-learning model to output an outlier score that represents a degree of deviation of performance data of the degradation performance items from a normal range;
• after the machine-learning period, applying the machine-learning model to target performance data of the degradation performance items to produce an outlier score for each of a plurality of cause events for each type of job and each execution period over a time period;
• and
• outputting information on each of the plurality of cause events based on a temporal change in the produced outlier scores over the time period.