Abstract: A method and apparatus for monitoring a system are provided. The method includes: acquiring a series of historical status index data of a monitored system during at least one data collection period; introducing the series of historical status index data into a pre-trained recommended feature extraction model to perform a matching operation, to obtain a feature extraction algorithm matching the series of historical status index data as a recommended feature extraction algorithm; determining a normal value range of feature values obtained by performing feature extraction on the series of status index data of the monitored system according to the recommended feature extraction algorithm; and monitoring the monitored system according to the recommended feature extraction algorithm and the normal value range.

Abstract: A system monitoring method and apparatus comprises: collecting periodically status indicator data of a monitored system to generate a status indicator data sequence; selecting predetermined pieces of status indicator data according to data collecting time in a reverse chronological order; determining a category from predetermined categories, the predetermined pieces of status indicator data belonging to the determined category; selecting, from the historical status indicator data, status indicator data belonging to the determined category and obtained in a collection period as characteristic data of the determined category; calculating a predicted value of a status indicator of the system at a predicting moment using the characteristic data; and determining whether the system is abnormal, based on a difference between the calculated predicted value and a true value of the status indicator of the system collected at the predicting moment.

Abstract: Disclosed are a method and apparatus for monitoring a system.

Abstract: The present disclosure provides a data predicting method and apparatus. The method comprises: acquiring at least one time factor of a prediction moment; predicting a desired value of data of the prediction moment according to a preset data model and said at least one time factor of the prediction moment. As compared with a method of predicting the desired value on a year-on-year basis or a month-on-month basis in the prior art, the above technical solution of the present disclosure may effectively improve the prediction accuracy of the desired value of the data of the prediction moment and thereby improve a monitoring effect of monitoring abnormality according to the desired value of the predicted data.

Abstract: A system monitoring method and apparatus comprises: collecting periodically status indicator data of a monitored system to generate a status indicator data sequence; selecting predetermined pieces of status indicator data according to data collecting time in a reverse chronological order; determining a category from predetermined categories, the predetermined pieces of status indicator data belonging to the determined category; selecting, from the historical status indicator data, status indicator data belonging to the determined category and obtained in a collection period as characteristic data of the determined category; calculating a predicted value of a status indicator of the system at a predicting moment using the characteristic data; and determining whether the system is abnormal, based on a difference between the calculated predicted value and a true value of the status indicator of the system collected at the predicting moment.