## 4 Dynamic Operation and Maintenance Map Construction  
The overall architecture of the dynamic operation and maintenance map is shown in Figure 3, which is divided into the data layer and service layer.  
The data layer includes data modeling, data access, data processing, and other steps, while the service layer provides data interfaces and visual displays.  
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2. Unify map data modeling [10; 11; 12; 13]: The data model is divided into node and edge design. In terms of the node model, clarify the node types and attributes of each node type, including unique KEYs (this method uses IPs for alarm point attachment). Node types are obtained by refining and combing the operation and maintenance object directory of distributed information systems, covering applications, systems, networks, devices, etc., including but not limited to applications, application groups, middleware, PODs, virtual machines, physical machines, network devices, etc. In terms of the relationship model, it is mainly divided into two categories, one is the application access level topology, as shown in Figure 4. It mainly describes the call relationship between applications, groups, and services. The other is the vertical resource dependency vertical topology, as shown in Figure 5. It mainly describes the deployment and operation dependency relationship from large to small at the resource level.  
Figure 3: Dynamic map architecture.  
Figure 2: Model architecture.  
Data access [14; 15] mainly includes four types of data, of which configuration management and network management mainly provide static basic device information data, used to build the \"skeleton\" of the basic environment, while network TCP flow and microservice call logs provide IP-level IT component intercommunication, as well as dynamic information of business calls, used to reflect the actual business deployment situation on top of the \"skeleton\".
3. Data processing [16; 17]: According to the four layers defined by the data model and the constraints between objects, information extraction and entity alignment are completed based on the multi-source data of the access module. In the process of data fusion, potential relationships are mined through intelligent algorithms for some missing relationships. Taking network switches as an example, some old devices cannot support neighbor discovery protocol (LLDP/CDP) data collection, resulting in missing topology connections. However, after introducing a similarity judgment intelligent model, the port connection relationship can be established by calculating the similarity of traffic rate trends on different ports. After introducing network simulation capabilities, cross-network connection relationships between system nodes can also be established through route table entry calculations. With the help of algorithms, the integrity of map data can be further improved, and self-learning capabilities can be built.
4. Data interface access and visualization display [18; 19]: Based on graph query, they provide data access interfaces and provide view display.  
Figure 4: Application access level topology data model.  
Figure 5: Resource-dependent vertical topology data model.