alt Hacker News> lets say it can process a request normally in 20us.
Then what if the OS/thread hangs? Or maybe a hardware issue even. Seems a bit weird to have critical path be blocked by a single mutex. That's a recipe for problems or am I missing something?
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Depending on what you want to do, there are ways to change where the blocking occurs, like https://blog.sequinstream.com/genserver-reply-dont-call-us-w...
Part of the problem with BEAM is it doesn't have great ways of dealing with concurrency beyond gen_server (effectively a mutex) and ETS tables (https://www.erlang.org/doc/apps/stdlib/ets). So I think usually the solution would be to use ETS if its possible which is kind of like a ConcurrentHashMap in other languages or to shard or replicate the shared state so it can be accessed in parallel. For read only data that does not change very often the BEAM also has persistent term (https://www.erlang.org/doc/apps/erts/persistent_term.html).
Hardware issues happen, but if you're lucky it's a simple failure and the box stops dead. Not much fun, but recovery can be quick and automated.
What's real trouble is when the hardware fault is like one of the 16 nic queues stopped, so most connections work, but not all (depends on the hash of the 4-tuple) or some bit in the ram failed and now you're hitting thousands of ECC correctable errors per second and your effective cpu capacity is down to 10% ... the system is now too slow to work properly, but manages to stay connected to dist and still attracts traffic it can't reasonably serve.
But OS/thread hangs are avoidable in my experience. If you run your beam system with very few OS processes, there's no reason for the OS to cause trouble.
But on the topic of a 15ms pause... it's likely that that pause is causally related to cascading pauses, it might be the beginning or the end or the middle... But when one thing slows down, others do too, and some processes can't recover when the backlog gets over a critical threshold which is kind of unknowable without experiencing it. WhatsApp had a couple of hacks to deal with this. A) Our gen_server aggregation framework used our hacky version of priority messages to let the worker determine the age of requests and drop them if they're too old. B) we had a hack to drop all messages in a process's mailbox through the introspection facilities and sometimes we automated that with cron... Very few processes can work through a mailbox with 1 million messages, dropping them all gets to recovery faster. C) we tweaked garbage collection to run less often when the mailbox was very large --- i think this is addressed by off-heap mailboxes now, but when GC looks through the mailbox every so many iterations and the mailbox is very large, it can drive an unrecoverable cycle as eventually GC time limits throughput below accumulation and you'll never catch up. D) we added process stats so we could see accumulation and drain rates and estimate time to drain / or if the process won't drain and built monitoring around that.