With the increasing popularity of block chain technology, higher requirements are put forward for the stability of consortium chain network and the interpretability of the transaction process. The requirements of network performance monitoring and analysis are summarized during the development and application of Fabric. A visual analysis method for Fabric performance situational awareness is designed. Through multi-view joint analysis from network topology graph, block height growth graph and transaction consensus animation, it supports exploration from three levels: network, node and transaction. A quantitative method for the performance of the Fabric network and nodes is proposed, and the performance situation is measured in the form of scores, which is convenient to understand the operation of the consortium chain, the difference in activity between channels and the health degree of nodes. Finally, through case study and user evaluation, it is proved that the method is practical and effective in the visual monitoring of Fabric, performance situational analysis and transaction consensus trajectory tracking.