This is cool but I'm struggling to think of a case where I'd want to run backend JavaScript in a memory constrained environment, doubly so where performance isn't a concern.
The bot is rarely used, so on average, it only uses 0.06% of my machine's CPU power. However, it consumes 3% of the RAM at the same time. --smol switch according to Jarred's tests reduces memory usage ~7 times by increasing CPU usage just 2x times. In my case such redistribution of resource consumption would be a clear win!
To save RAM, I actually switched to a 32-bit Python base image. This switch resulted in a 30% reduction in RAM usage.
Maybe launching lots of separate services/containers locally, just to have the ability to debug everything and step through how a request travels through all of the services in one go, with multiple IDE instances also open locally, in addition to other stuff?
Distributed tracing is nice for remote environments, but having 5-20 IDE instances open with all of the related services can also provide a nice debugger experience. Not every machine has ample RAM for this, though, so I guess it's nice to have the option, without the processes/containers running into OOM so much?