Cheap and Cheerful

Hot on the heels of OpenAI, Google has shipped an agent orchestration system of its own. It runs on Kubernetes, naturally. The pitch is billions of agents per cluster, each in its own isolated environment.

Isolating the agent's environment is an unqualified good, and it happens to be exactly what I had been working on. The first version of my orchestrator (much like the beta of Claude Code's own orchestrator) simply ran agents as processes in tmux, all in the same environment.

That was poverty, not design: they had to run on whatever hardware is lying around my house, from my laptop to my son's gaming PC (inside WSL).

For real production, though, that obviously will not fly. So having studied what Google came up with, my first instinct was to use it in my orchestrator (ripping out Nomad and NATS), and I immediately tripped over Kubernetes.

Not that I am a hater, but I have always believed that the closer to the metal a system runs, the more efficient and simpler it is, and Kubernetes is a brutal pile of abstractions.

Digging further, I saw that Google is solving a different problem: where an agent should live. Mine is how to work with it. The only overlap is the Nomad layer, and swapping it for their stack would mean trading the scheduler and the message bus for a Kubernetes cluster.

So I settled on LXC containers in Proxmox: cheap and cheerful, and above all simple. The new version of MOP adds an abstraction layer over the container runtime, with LXC-on-Proxmox support built on top of it. Enjoy.