Tinygo made a lot of progress over the years -- e.g. they've recently introduced macOS support!

It does indeed produce much smaller binaries, including for macOS.

  yuriy@MacBookAir ~/t/tinygo> time tinygo build -o test-tiny main.go
  
  ________________________________________________________
  Executed in    1.06 secs    fish           external
     usr time    1.18 secs    0.31 millis    1.18 secs
     sys time    0.18 secs    1.50 millis    0.18 secs
  
  yuriy@MacBookAir ~/t/tinygo> time go build -o test-normal main.go
  
  ________________________________________________________
  Executed in   75.79 millis    fish           external
     usr time   64.06 millis    0.41 millis   63.64 millis
     sys time   96.76 millis    1.75 millis   95.01 millis
  
  yuriy@MacBookAir ~/t/tinygo> ll
  total 5096
  -rw-r--r--@ 1 yuriy  staff    74B  3 Apr 19:17 main.go
  -rwxr-xr-x@ 1 yuriy  staff   2.3M  3 Apr 19:18 test-normal*
  -rwxr-xr-x@ 1 yuriy  staff   192K  3 Apr 19:18 test-tiny*
  yuriy@MacBookAir ~/t/tinygo> cat main.go
  package main
  
  import "fmt"
  
  func main() {
          fmt.Printf("Hello world!\n")
  }

We're using TinyGo and the Wazero runtime for our WASM plugin system in ServiceRadar, highly recommend both if you're using golang.

Wazero is awesome. For anyone wanting to embed in languages other than Go, check out Extism.

Yay wazero maintainer here, thanks for the shout-out!

Writing embedded code with an async-aware programming language is wonderful (see Rust's embassy), but wonder how competitive this is when you need to push large quantities of data through a micro controller, I presume this is not suitable for real-time stuff?

Can you elaborate on this and how it would be different from signaling on interrupts and DMA?

Hardware-level async makes sense to me. I can scope it. I can read the data sheet.

Software async in contrast seems difficult to characterize and reason about so I've been intimidated.

I've written a fair amount of code for EmbeddedGo. Garbage Collector is not an issue if you avoid heap allocations in your main loop. But if you're CPU bound a goroutine might block others from running for quite some time. If your platform supports async preemption, you might be able to patch the goroutine scheduler with realtime capabilities.

We're streaming RSTP camera feeds through WASM plugins and host-bridge adapters, no problem. I was surprised how well it worked TBH.

https://code.carverauto.dev/carverauto/serviceradar/src/bran...

You can disable GC in tinygo, so if you allocate all the necessary buffers beforehand it can have good performance with real-time characteristics. If you _need_ dynamic memory allocation then no, because you need GC it can't provide realtime guarantees.