blog-comments VS rupy

This was a great article, very easy to understand without leaving out the fundamental pieces (the saga that is async implementation difficulty). I think I can even boil this situation down to Rust having it's Monad moment.

It's in this (HN) comment thread and a bunch of informed comments on the original article:

https://github.com/eeeeeta/blog-comments/issues/10#issuecomm...

https://github.com/eeeeeta/blog-comments/issues/10#issuecomm...

https://github.com/eeeeeta/blog-comments/issues/10#issuecomm...

The comments are correct in my view -- Rust can't/shouldn't do what Haskell did, which was to create use a general purpose abstraction that is essentially able to carry "the world" (as state) along with easy-to-trade chained functions on that state (whenever it gets realized). Haskell might have solved the problem, but it has paid a large price in language difficulty (perceived or actual) because of it, not mentioning the structural limitations of what Rust can do and it's constraints. The trade-off just isn't worth it for the kind of language Rust aims to be.

Realistically, I think this issue is big but not enough to write off rust for me personally (as the author seems to have) -- I'd just do the move + Arc shenanigans because if you've been building java applications with IoC and/or other patterns that generally require global-ish singletons (given example was a DB being used by a server), this isn't the worst complexity trade-off you've had to make, though the Rust compiler is a lot more ambitious, and Rust has a cleaner, better, more concise type system as far as I'm concerned.

I think another thing I've gained from this article is another nice little case where Haskell (if you've taken the time to grok it sufficiently, which can be a long time) offers a bit of a nicer general solution than Rust, assuming you were in a world where those two were actually even substitutes. In the much more likely world where you might compare Rust and Go2, this might be a win for Go2, but the rest of the language features would put rust on top for me.

I have been running a Raspberry 2 cluster for 10 years: http://host.rupy.se

A few weeks back the first SD card to fail got so corrupted it failed to reboot!

My key learning is use oversized cards, because then the bitcycle will wear slower!

I'm going from 32GB to 256/512/1024!

How this article does not mention SSE, comet or chunking escapes me.

What does their definition of event-driven really look like in practice.

Nobody has a clue.

Here is the ideal event driven system, it's async-to-async: https://github.com/tinspin/rupy/wiki/Fuse

The example is not working because I had to shut down the services for multiple reasons, but the high level of it is that you use 4 (potentially different) threads to do one request/response middle man transaction.

That way you have _zero_ io-wait or idling. I'm surprised nobody has copied this approach since I invented it 10 years ago. I understand why though you need your entire chain to be async and that means rewriting everything and that is a big risk when it's hard to debug.

But if you succeed you can build something that is 10x perf/watt than all other implementations. Which is going to be important when interest rates go higher and crash our entire industry.

The hardware is peaking.

So software is where you can make the difference: http://host.rupy.se

I think we're all confused over the definition. Also one might understand what all the proponents are talking about better if they think about this more as a process and not some technological solution:

https://github.com/tinspin/rupy/wiki/Process

All input I have is you want your code to run on many machines, in fact you want it to run the same on all machines you need to deliver and preferably more. Vertically and horizontally at the same time, so your services only call localhost but in many separate places.

This in turn mandates a distributed database. And later you discover it has to be capable of async-to-async = no blocking ever anywhere in the whole solution.

The way I do this is I hot-deploy my applications async. to all servers in the cluster, this is what a cluster node looks like in practice (the name next to Host: is the node): http://host.rupy.se if you click "api & metrics" you'll see the services.

With this not only do you get scalability, but also redundancy and development is maintained at live coding levels.

I have hosted my own web server both physically and codevise since 2014.

It's on a Raspberry 2 cluster:

http://host.rupy.se

Since 2016 i have my own database also coded from scratch:

http://root.rupy.se

We need to implement HTTP/1.1 with less bloat, a C non-blocking web server that can share memory between threads is probably the most interesting project for humans right now, is anyone working on that?

I have one in Java: https://github.com/tinspin/rupy

Here is the 2000 lines of code of the entire database: http://root.rupy.se/code?path=/Root.java

And here you can try it out: http://root.rupy.se

The smallest PaaS you have ever seen is one order of magnitude larger than mine: https://github.com/tinspin/rupy

And I bet you the same goes for performance, if not two!

The data is here: http://fuse.rupy.se/about.html

Under Performance. Per watt the fuse/rupy platform completely crushes all competition because of 2 reasons:

- Event driven protocol design, averages at about 4 messages/player/second (means you cannot do spraying or headshots f.ex. which is another feature in my game design opinion).

- Java's memory model with atomic concurrency which needs a VM and GC (C++ copied that memory model in C++11, but it failed completely because they lack both VM and GC, but that model is still to this day the one C++ uses), you can read more about this here: https://github.com/tinspin/rupy/wiki

You can argue those points are bad arguments, but if you look at performance per watt with some consideration for developer friendlyness, I'm pretty sure in 100 years we will still be coding minimalist JavaSE on the server and vanilla C (compiled with C++ compiler) on the client.