I can only assume you're probably referring to some of these things:
1. Response latency, esp at 99%-ish mark, under load 2. Memory usage per connection under many idle connections 3. Scalability wrt. data sharing, backing persistent data, replication/redundancy strategies, etc
I'm not sure if you were referring to us, the diesel authors, when you indicated that someone didn't understand something about Comet scaling, but I assure you that diesel does 1 and 2 quite nicely, as do most sensibly-written things based on epoll, kqueue, etc. The benchmark page is with 1k concurrent connections, and it does well with more than that, too.
If you're referring to item 3, I'm afraid diesel doesn't tackle that element of scalability yet. It's more of an I/O library, not really a framework with aspirations of providing high availability. We have some plans and quite a bit of mostly-working code that implements a paxos-based framework for achieving those goals as well, but release of that part of the framework is some months out.
Writing good unit tests for this stuff is a higher priority--unit testing async code is a PITA. We're probably going to need to steal ideas from twisted.trial or something.
Thanks for checking out diesel.