Simplifying container and AI development on RHEL 10 with Podman Desktop

So for years I've used Docker Compose as my stepping stone to k8s. If the project is small, or mostly for my own consumption OR if the business requirements don't really support the complexity of k8s, I use Compose. It's simple to manage with bash scripts for deployments, not hard to setup on fresh servers with cloud-init and the process of removing a server from a load balancer, pulling the new container, then adding it back in has been bulletproof for teams with limited headcount or services where uptime is less critical than cost control and ease of long-term maintenance. You avoid almost all of the complexity of really "running" a server while being able to scale up to about 20 VMs while still having a reasonable deployment time.

Think Python is an introduction to Python for people who have never programmed before – or for people who have tried and had a hard time. You can order print and ebook versions of the third edition from Bookshop.org and Amazon.