I agree completely. It is frustrating that no decent books have been written regarding scaling architectures/strategies with current tooling. One has to scavenge various blog posts to try and discover ideas that might help solve their growth issues. I would love to see a book that covers scaling for app servers, RDBMSes, NoSql dbs, using queues/messaging effectively, etc. Failing that, I'd like to see something like Scalers at Work (a la Coders at Work) which would interview different devs who had to solve scaling issues.
Look for local meetups - in Seattle there's "Seattle Scalability" which is great for this sort of thing (and highscalability used to be great for this, too).
Not the parent, but the linked material is more foundational than the subject matter raised in the post. There is in fact an appreciable lack of good, battle-tested, non-secret, sometimes-but-not-necessarily anecdotal public info about the part of the design process where you have a working system doing fairly okay, but you know you're inches away from a very unpleasant wall. On fire [1].
It doesn't help that distributed systems are a dark art, that many open source and free-to-use tools that developers have access to gate the HA/clustering features behind steep pricing (though I sympathize it's one of the few effective ways to make money in open source), and that expertise with scaling is very often a competitive advantage.
The first part is mainly about erlang and the choices they made. But the last part is not at all specific to erlang and walk you all the way through all decisions to take to build that type of architecture.
I agree completely. It is frustrating that no decent books have been written regarding scaling architectures/strategies with current tooling. One has to scavenge various blog posts to try and discover ideas that might help solve their growth issues. I would love to see a book that covers scaling for app servers, RDBMSes, NoSql dbs, using queues/messaging effectively, etc. Failing that, I'd like to see something like Scalers at Work (a la Coders at Work) which would interview different devs who had to solve scaling issues.