If you use SCC, then you don't need a separate MQ - That is only if you want to do things yourself manually. I will update the docs to make that clearer.
It should only take a few minutes to deploy a cluster across hundreds of machines. The only limit is the maximum number of hosts that Kubernetes itself can handle (which is I think is over 1000 now)? SCC is self-sharding and runs and scales itself automatically with no downtime.
You can easily handle 5 million concurrent users with a small cluster. SC's problem isn't scalability, it's marketing.
That's perfectly fair; fix the marketing then. :P In evaluating a solution, the marketing is the -first thing- anyone looks at. And how it currently reads, "SocketCluster only provides you the interface for synchronizing instance channels - It doesn't care what technology/implementation you use behind the scenes to make this work" definitely reads as "You need a technology/implementation behind the scene" rather than "we provide you a default one, and you can swap it out".
For me to pick Socketcluster for a distributed solution (or more broadly, what I'd want for -any- technical solution) I'd want to know what else I need to pair it with (which the docs actually mislead me on), what else I can benefit from (which the docs don't tell me, but which does exist per your links), and what benefits I stand to get from using it (the docs tell me only marketing claims, but with no metrics, performance, data, etc, for what happens in a distributed context, well, I would avoid it).
Ideally, set up a clustered performance test, and then make as many of the artifacts (docker images, configs, readme, etc) available so others can conduct the same performance test themselves (as well as have a reference architecture for their own solution). Heck, if you're doing it in AWS, consider making the AMIs available along with whatever modifications need to happen. -That- would be very convincing for someone looking to adopt a solution in this space, if they could literally just spin up some EC2s and immediately start throwing load at a fully configured cluster.
Also, to make it clear, is this handling message passing between instances in the cluster?
Yes, it handles message passing between instances in the cluster. That means if you publish a message on a channel whilst connected to one host, the message will also reach subscribers to that channel which are on any other host in the cluster. It shards all channels across available brokers, when you scale up the number of brokers, it will automatically migrate the shards across available brokers with no downtime.
Okay, nice. Then yeah, given some performance benchmarks showing some numbers at increasing number of nodes, with messages being broadcast across 1-to-1 channel pairings (i.e., direct message), 1-to-100 (for groups), and 1-to-all, I think it could sell itself as a pretty compelling turnkey solution (barring the scc-state concern which you're aware of).
Possibly also consider some testing and documentation around geographic distribution; what happens if the nodes are located in different datacenters with non-trivial latency between them? Is that an issue? In the event of netsplits, does it split brain (probably not, given scc-state, but addressing that might cause it to)? That might be fine, it might not, depending on the use case, and just documenting what happens (by default, at least, if it's to be tunable) would be helpful as well.
It should only take a few minutes to deploy a cluster across hundreds of machines. The only limit is the maximum number of hosts that Kubernetes itself can handle (which is I think is over 1000 now)? SCC is self-sharding and runs and scales itself automatically with no downtime.
You can easily handle 5 million concurrent users with a small cluster. SC's problem isn't scalability, it's marketing.