Agreed on all parts.
The Erlang and OTP manuals were very nicely written, and I was able to reason about most aspects of the system pretty well from reading them.
I did a bit more research after writing up my comment (my mind got a bit too focused on it to let it go) and found this great resource about handling various system load scenarios: https://ferd.ca/handling-overload.html
I'll +1 your pragmatic comment on not adopting tools just because they're there.
Again I no longer work in Erlang, but I find the systems, architecture, and problem solving particularly interest piquing.
Now I'm off to look up production use-cases where Mnesia was the most pragmatic solution.
Fred's blog, and Learn You Some Erlang for Great Good are invaluable, but on the topic of production systems, his ebook Erlang In Anger (https://www.erlang-in-anger.com/) is excellent as well - honestly it's hard to overstate just how much good he's done for the community in terms of documenting and philosphizing about Erlang, architecture and operating production systems. He's solid gold!
The ability to format MNesia tables in such a way that exporting them over SNMP is trivial was an absolute joy to work with for me about 12 years ago!
I was able to stand up a quick management solution for a rather complex system as a one-person team using a combination of Erlang, MNesia, and port drivers to various back-ends written in Python, C, C++ and Haskell. It was the most productive I think I've ever been on any project in my entire career so far.
And I'd love to get back to that feeling of just kicking ass every day.
I did a bit more research after writing up my comment (my mind got a bit too focused on it to let it go) and found this great resource about handling various system load scenarios: https://ferd.ca/handling-overload.html
I'll +1 your pragmatic comment on not adopting tools just because they're there.
Again I no longer work in Erlang, but I find the systems, architecture, and problem solving particularly interest piquing.
Now I'm off to look up production use-cases where Mnesia was the most pragmatic solution.