JupyterHub en Kubernetes

On Thursday, March 13, Marcos Rodrigo and Daniel Fuertes, researchers from the rupo de Tratamiento de Imágenes (GTI), presented a new cloud computing service for the Department of Signals, Systems, and Radiocommunications (SSR) at the School of Telecommunications Engineering (ETSIT). The presentation, titled "New Cloud Computing Service (GPUs) of SSR: Presentation and User Guide," took place in Building A, SSR Laboratory, A201L, Room C, at 11:00 AM.

A New Service for the Academic Community

The main objective of this presentation was to introduce the new cloud computing service of SSR, designed to facilitate work with Deep Learning applications. This service will allow department members to use a system based on open-source solutions, similar to Google Colab, but hosted in the SSR teaching laboratory.

Presentation Content

Under the subtitle "JupyterHub on Kubernetes: Practical Guide for University Researchers in Cloud Computing Environments," Marcos and Daniel provided a detailed guide on how to use this new platform. During the presentation, the following key points were covered:

• • • • Basic Access: Secure login/logout, password change, and session management.
      • Practical Configuration: Creating virtual environments for projects, running code, and managing files.
      • Efficient Resource Usage: How to utilize and monitor GPU resources (CUDA), storage management, among others.

Benefits and Applications

This new service is specifically aimed at research teams that require a stable, scalable platform with no time restrictions for the development of projects in artificial intelligence, data analysis, and intensive computing.

With this initiative, SSR strengthens its commitment to innovation and technological development, providing advanced tools for the ETSIT academic community.