A cloud-accessible virtual lab architecture for teaching network automation: Integrating Cisco packet tracer REST API with docker, Cloudflare tunnel, and Google Colab

This study designed and evaluated a reproducible, cloud-accessible virtual laboratory architecture for teaching network automation in higher education. The goal was to address the lack of cost-effective and scalable infrastructures that enable students to develop automation skills aligned with current industry demands. The proposed design integrated Cisco Packet Tracer’s REST API, Docker containerization, Cloudflare Tunnel, and Google Colab to facilitate real-time programmatic interaction with simulated networks through Python. A design-based research (DBR) methodology was adopted, and a pilot was conducted with 35 undergraduate students enrolled in the “Network Management” course at the Technical University of Machala (Ecuador). The intervention consisted of three structured labs, a pre-test/post-test assessment, and a perception survey. Findings revealed statistically significant learning gains, with post-test scores showing marked improvement over pre-test results. Students also reported high satisfaction and engagement, highlighting the accessibility and novelty of combining cloud platforms with network simulators. The study concludes that this architecture provides a feasible and pedagogically sound model for integrating network automation into curricula. Practical implications include lowering barriers to access, fostering active learning, and offering institutions a scalable, low-cost alternative to physical labs.