Nous recrutons un·e ingénieur·e en informatique pour travailler à l’application des concepts et technologies DevOps (conteneurs Docker, Git, Linux, libre, …) pour la mise au point et l’hébergement de dispositifs de Travaux Pratiques virtualisés, qui seront utilisés pour des enseignements d’informatique et de réseaux, sur un CDD de 1 an, à Télécom SudParis, à Évry (91).
Pour en savoir plus, voir le descriptif du poste que j’ai mis en ligne.
I’ve recorded a screencast: Labtainers in docker demonstration (embedded below) demonstrating how I’ve tweaked Labtainers so as to run it inside its own Docker container.
I’m currently very much excited by the Labtainers framework for delivering virtual labs, for instance in the context of MOOCs.
Labtainers is quite interesting as it allows isolating a lab in several containers running in their own dedicated virtual network, which helps distributing a lab without needing to install anything locally.
My tweak allows to run what I called the “master” container which contains the labtainers scripts, instead of having to install labtainers on a Linux host. This should help installation and distribution of labtainers, as well as deploying it on cloud platforms, some day soon. In the meantime Labtainer containers of the labs run with privileges so it’s advised to be careful, and running the whole of these containers in a VM may be safer. Maybe Labtainers will evolve in the future to integrate a containerization of its scripts. My patches are pending, but the upstream authors are currently focused on some other priorities.
Another interesting property of labtainers that is shown in the demo is the auto-grading feature that uses traces of what was performed inside the lab environment by the student, to evaluate the activities. Here, the telnetlab that I’ve shown, is evaluated by looking at text input on the command line or messages appearing on the stdout or in logs : the student launched both telnet or ssh, some failed login appeared, etc.
However, the demo is a bit confusing, in that I recorded a second lab execution whereas I had previously attempted a first try at the same telnetlab. In labtainers, traces of execution can accumulate : the student wil make a first attempt, and restart later, before sending it all to the professor (unless a redo.py is issued). This explanes that the grading appears to give a different result than what I performed in the screencast.
Stay tuned for more news about my Labtainers adventures.
P.S. thanks to labtainers authors, and obs-studio folks for the screencast recording tool 🙂