Evaluation of Cloud Platform Operation and Maintenance Time Series Knowledge Graph State by Integrating Knowledge Graph and Graph Learning

Cloud computing platforms have become an important infrastructure for modern enterprises to build business architectures, but with the continuous expansion of cloud platform scale, the difficulty of operation and maintenance has also increased exponentially. In order to better manage operation and maintenance data and improve operation and maintenance efficiency, this paper proposes a cloud platform operation and maintenance temporal knowledge graph state evaluation that integrates knowledge graph and graph learning. Based on the knowledge graph theory, a cloud platform operation and maintenance knowledge graph is constructed based on Sentence BERT, and the general static knowledge graph is extended to temporal knowledge graph, A graph convolutional neural network based reasoning method for cloud platform operation and maintenance temporal knowledge graph has been proposed. Through the above methods, the cloud platform operation and maintenance system can effectively capture the changes in temporal data and node feature information, improving the efficiency and quality of cloud platform operation and maintenance.