I have a small homelab running a few services, some written by myself for small tasks - so the load is basically just me a few times a day.
Now, I’m a Java developer during the day, so I’m relatively productive with it and used some of these apps as learning opportunities (balls to my own wall overengineering to try out a new framework or something).
Problem is, each app uses something like 200mb of memory while doing next to nothing. That seems excessive. Native images dropped that to ~70mb, but that needs a bunch of resources to build.
So my question is, what is you go-to for such cases?
My current candidates are Python/FastAPI, Rust and Elixir, but I’m open for anything at this point - even if it’s just for learning new languages.
Are you planning to compile the programs on the thin client? Although rust runs efficiently on a lot of hardware, compiling is gut-wrenching.
I have an rPi 1B running as a lightweight server and both rust and c++ applications take hours to compile (some of them take over a DAY). so, interpreted languages might be what you’re looking for. my favorite is python. most distros have a lot of native packages in their repos. albeit a little weird to work on, perl is great, too.
To add to this, with rustup you can add different build targets than the current system - could let you build the binary on a more powerful pc and then just scp it over.
Yeah, we do this regularly at $DAYJOB, although we use Cross.
Basically, if you pull in any libraries with vendored C code, like e.g. OpenSSL, then you’d need to configure a linker and set up cross-compilation for C code.
Cross does the whole compilation in a container where this is already set up, so you just need to install Docker or Podman on your host system.
Basically:
…and out plops your binary for a Raspberry Pi.
this is great.