I think you're ignoring the fundamental issue when deploying container based services v/s services on a multiple VM's. Usually, the architecture for containers involves spinning up a bunch of VM's and deploying some kind of layer on top of that (either K8s or Swarm or something else). When you deploy containers, they may not be on the same VM, or the overlay network itself may require some kind of communication to another container on another VM. This usually creates a lot more communication b/w hosts and rate limiting becomes the bottleneck.

Do you have any evidence of this rate-limiting showing that it's that much of a problem? People have been running clustered apps on EC2 for over a decade and it's not like you hear people saying you can't run Cassandra, ElasticSearch, etc. on EC2 because the network is limited.

Similarly, do you have any data showing that a container system has such incredible overhead compared to the actual application workload? I mean, if that was true you'd think the entire Kubernetes team would be staying up nights figuring out how to reduce overhead.

You run a compute pool, you don't spin up EC2 instances on demand for this kind of application. You scale the pool based on target utilization metrics.