Toward Building a Semantic Network Inventory for Model-Driven Telemetry

Abstract: Network telemetry based on data models is expected to become the standard mechanism for collecting operational data from network devices efficiently. But the wide variety of standard and proprietary data models along with the different implementations of telemetry protocols offered by network vendors, become a barrier when monitoring heterogeneous network infrastructures. To facilitate the integration and sharing of context information related to model-driven telemetry, this work proposes a semantic network inventory that integrates new information models specifically developed to capture context information in a vendor-agnostic fashion using current standards defined for context management. To automate the integration of this context information within the network inventory, a reference architecture is designed. Finally, a prototype of the solution is implemented and validated through a case study that illustrates how the network inventory can ease the operation of model-driven telemetry in multi-vendor networks.