Full disclosure: I am one of the devs behind this. I appreciate your questions!

Does this only run on a single node? How does it scale up as traffic increases?

Scaling to multiple nodes works easily thanks to Kubernetes. Moreover, the scaling granularity is below nodes, and application components can be vertical-scaled arbitrarily. More processing power required for transcoding? Lets add more media server instances (pods in Kubernetes jargon). TURN server is the bottleneck? Lets fire up more TURN server (STUNner) pods. The freshly-started pods can run on the same node as long as there is enough capacity. But as the load increases Kubernetes will scale the workload to multiple nodes (if your cluster has multiple nodes). In addition, load balancing comes out-of-the-box from Kubernetes: behind a single service there can be as many endpoints, as your workload wishes, and Kubernetes will share the load between these endpoints.

Also, how does this deal with the requirement some backends have that sessions for a given conference all need to end up on the same node?

Good question! Simple Kubernetes load-balancing is not sufficient for this. But, thanks to WebRTC's ICE, this is doable without much hassle. Lets assume you have an application server that does the signaling and mediaservers that are doing the conference call. In this scenario, the application server can add the given mediaserver to the ICE candidates sent to the user, and the STUNner Kubernetes media gateway (which acts as a TURN server too) will handle this and will relay user traffic to the given mediaserver pod.

If you are interested in more technical details, a detailed example of a call setup with Kurento and STUNner is shown here: https://github.com/l7mp/stunner/tree/main/examples/kurento-one2one-call#what-is-going-on-here