This solution deploys a web-based training environment to create learning content. It is well suited for training on server side technologies and system administration such as Kubernetes, Docker or Terraform trainings. Based on Jupyter Notebooks, a well-known tool for data science and machine learning, it provides a web-based interface which allows trainers to build and share interactive content, including code, commands lines and explanations, making it easier for learners to understand and practice concepts in a hands-on manner.

This image is designed to be deployed and managed through the TFLab Solution which automates the deployment for training environments on Azure.

Image comes with the following pre-installed packages and configurations:

- Ubuntu 24.04 LTS

- Traefik, for local reverse proxy and local TLS termination

- JupyterLab, for web-based training environment

- bash_kernel, to run bash commands in JupyterLab

- Docker, for container trainings

- KinD (Kubernetes in Docker), for Kubernetes trainings

- Terraform, for infrastructure as code trainings

Once the VM is started, you can access the JupyterLab web environment in various ways, depending on the configuration you choose:

- if you rely on a fully private network, URL will look like *https://

- if you set a custom domain to the public IP of the VM, URL will look like *https://

Connection to the Jupyter Lab environment requires a password which is generated on first boot of the VM instance.

Password is printed on /var/log/syslog and saved in the Home directory of the admin user.

You can also use the "Run Command" method to execute "cat /home/