Network Monitoring Frameworks for Enterprise IT Infrastructure

Enterprise IT infrastructure produces large volumes of telemetry from routers, switches, firewalls, servers, virtual machines, storage systems, cloud resources, security appliances, and application services. In many organizations, these sources are monitored through separate tools. As a result, alert duplication increases, operational context becomes fragmented, diagnosis takes longer, and the originating source of service disruption is harder to identify. This paper presents a unified network monitoring framework for enterprise IT infrastructure that integrates telemetry collection, preprocessing, anomaly detection, event correlation, root-cause analysis, and dashboard-based visualization within one architecture. The proposed method places heterogeneous operational data into a common analytical structure and evaluates system condition through threshold logic and health-oriented anomaly scoring. It then groups related alerts into incident clusters using temporal proximity, topology relationships, service dependencies, and asset similarity. The results show broader visibility across network, host, cloud, and security layers, along with lower alert noise and clearer incident summaries. The anomaly detection stage produced stable results under routine and fault conditions, while the correlation stage reduced redundant alerts during burst scenarios. Root-cause ranking also provided a clearer path from visible symptoms to initiating faults. Overall, the study shows that an integrated monitoring framework can improve operational interpretation, incident handling, and infrastructure visibility in complex enterprise IT environments.