NetGraf: A Collaborative Network Monitoring Stack for Network Experimental Testbeds

Student: Divneet Kaur (University of California, San Diego)
Supervisor: Mariam Kiran (Lawrence Berkeley National Laboratory)

Abstract: Network performance monitoring collects heterogeneous data such as network flow data to give an overview of network performance, and other metrics, necessary for diagnosing and optimizing service quality. However, due to disparate and heterogeneity, to obtain metrics and visualize entire data from several devices, engineers have to log into multiple dashboards. In this paper we present NetGraf, a complete end-to-end network monitoring stack, that uses open-source network monitoring tools and collects, aggregates, and visualizes network measurements on a single easy-to-use real-time Grafana dashboard. We develop a novel NetGraf architecture and can deploy it on any network testbed such as Chameleon Cloud by single easy-to-use script for a full view of network performance in one dashboard. This paper contributes to the theme of automating open-source network monitoring tools software setups and their usability for researchers looking to deploy an end-to-end monitoring stack on their own testbeds.

ACM-SRC Semi-Finalist: no

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