The invention discloses an IT asset
fault propagation prediction method and
system based on dynamic evolution of a
knowledge graph, and relates to the technical field of
cloud computing and large-scale IT operation and
maintenance management. Through an asynchronous message
bus and a logic
clock, the
knowledge graph is updated immediately when resources are abnormal and a scheduling event occurs; the
knowledge graph uniformly integrates physical connection, logic dependence and multi-copy redundancy, so that the cross-
machine-room asset relationship is clear at a glance. And then, based on a weighted
logistic regression model, node features and relation weights in the knowledge graph are fused, the node
fault probability is accurately calculated, the limitation of traditional single-
dimensional analysis is solved, self-healing operation is supported, end-to-end intelligent operation and maintenance from fault detection to prediction and early warning to closed-loop self-healing are realized, and the fault detection efficiency is improved. The problems that in a cross-
machine-room and multi-live-site environment, resource topology is split, real-time state and alarm information cannot be fused with an asset dependence model, and large-scale real-time deployment of a traditional single-dimensional
fault analysis and high-complexity prediction
algorithm is difficult are effectively solved.