Comment by thayne
That's just not true. Distributed software is much more complicated and difficult than non-distributed software. Distributed systems have many failure modes that you don't have to worry about in non-distributed systems.
Now maybe you could have an abstraction layer over your storage layer that supports multiple data stores, including a distributed one. But that comes with tradeoffs, like being limited to the least common denominator of features of the data stores, and having to implement the abstraction layer for multiple data stores.
I’m a distributed systems architect. I design, build, and operate distributed systems.
> Distributed systems have many failure modes that you don't have to worry about in non-distributed systems.
Yes, but as previously mentioned, those failure modes are handled by abiding a few simple principles. It’s also worth noting that multiprocess or multithreaded software have many of the same failure modes, including the one discussed in this post. Architecting systems as though they are distributed largely takes care of those failure modes as well, making even single-node software like Jellyfin more robust.
> Now maybe you could have an abstraction layer over your storage layer that supports multiple data stores, including a distributed one. But that comes with tradeoffs, like being limited to the least common denominator of features of the data stores, and having to implement the abstraction layer for multiple data stores.
Generally I just target storage interfaces that can be easily distributed—things like Postgres (or maybe dqlite?) for SQL databases or an object storage API instead of a filesystem API. If you build a system like it could be distributed one day, you’ll end up with a simpler, more modular system even if you never scale to more than one node (maybe you just want to take advantage of parallelism on your single node, as was the case in this blog post).