With the development of the computing and networking convergence environment, service deployment has gradually adopted a graph-structured service function chaining (SFC) approach. In this context, service anomalies may arise from multiple factors such as nodes, networks, and service components. Due to the close correlation among various levels of indicators, it is often difficult to identify the root cause of the anomaly among them, making anomaly analysis and insight more challenging. Therefore, this paper aims to study a network telemetry-based anomaly diagnosis visualization method to improve the efficiency of network administrators in locating the root cause of anomalies in complex computing and networking convergence environments. Through the anomaly diagnosis visualization module developed in this study, network administrators can intuitively understand the abnormal conditions and impact scope in the system, thus locating the root cause of the anomalies more effectively.