The present invention relates to the technical field of operation and
maintenance management, and specifically relates to an integrated operation and
maintenance management system and method based on AIOps; the method includes: collecting multi-source IT operation and maintenance data and completing standardized preprocessing to form operation and maintenance
data input in a unified format; classifying and storing the preprocessed data using a
hybrid storage architecture, and implementing
data synchronization through a cross-
database synchronization tool to break data silos; performing intelligent analysis on the data based on the TensorFlow framework to generate fault diagnosis results and performance
trend prediction data; generating operation and maintenance decisions according to the analysis results, and performing automatic repair, work order allocation or
resource scheduling operations; outputting operation and
maintenance management results, presenting data and decision execution situations through a
visualization interface, and providing
report generation and management configuration functions; through a full-process
automated data processing and intelligent operation and maintenance decision-making mechanism with multi-module
collaboration, the technical problems of slow fault response, weak
data integration, low accuracy of risk prediction and low operation and maintenance efficiency in the traditional operation and
maintenance mode are solved.