DinoGlue

Our project, DinoGlue, is an all-in-one network testing solution developed for our sponsor, L3Harris, a company with a vast network infrastructure where performance and reliability are crucial. To ensure their networks performs optimally, L3Harris uses Network Traffic Generators (NTGs)—specialized tools designed to simulate network traffic and stress-test network components. While these NTGs are powerful at generating traffic, they often require manual configuration and scripting, making it difficult to automate and manage the entire testing process.

DinoGlue solves this problem by providing a unified platform that simplifies the process of configuring, executing, and analyzing network performance tests. Rather than focusing solely on generating traffic, DinoGlue streamlines the full testing workflow, from test configuration to result analysis. This automation reduces errors, accelerates testing cycles, and helps network engineers make data-driven decisions based on comprehensive, real-time insights.

This project was completed through the Senior Capstone Program in Computer Science at the University of Utah’s Kahlert School of Computing. The capstone is a two-semester course where student teams design, build, and deliver real-world software solutions. Our project was sponsored by L3Harris, who provided a specific problem for us to solve and supported us throughout the development process. 

Rust – High-performance backend with asynchronous execution via Tokio

Next.js – Responsive React-based frontend

TimescaleDB – Scalable time-series data layer built on PostgreSQL

Grafana – Rich dashboards for visualizing test results

Python – Interface for scripting and interaction with the Cisco TRex Network Traffic Generator

TCL - Interface for scripting and interaction with Ixia Network Traffic Generators

Docker – Docker toolchain integration, from custom Dockerfiles to Compose stack and network/volume management.