enctool VS rupy

https://concise-encoding.org/ is looking for help!

I'm planning to release v1 later this year, and there are still a number of things to finish:

- Finish upgrading the portable testing rig (whereby the tests are defined in CTE format so that they can be run against any implementation).

- Bring the Antlr grammar files up to date and make sure they're as easy as possible to build CTE parsers from.

- Add schema validation support to https://github.com/kstenerud/enctool for Concise Encoding documents (using https://cuelang.org/)

- Critiques on the format itself (passages that are unclear or don't make sense, features that shouldn't be there or need more work, etc)

- Implementations in other languages & platforms (CBE is more important to start because one can always use enctool to convert between CBE and CTE).

It's still in the prerelease stage, but v1 will be released later this year. I'm mostly getting hits from China since they tend to be a lot more worried about security. I expect the rest of the world to catch on to the gaping security holes of JSON and friends in the next few years as the more sophisticated actors start taking advantage of them. For example https://github.com/kstenerud/concise-encoding/blob/master/ce...

There are still a few things to do:

- Update enctool (https://github.com/kstenerud/enctool) to integrate https://cuelang.org so that there's at least a command line schema validator for CE.

- Update the grammar file (https://github.com/kstenerud/concise-encoding/tree/master/an...) because it's a bit out of date.

- Revamp the compliance tests to be themselves written in Concise Encoding (for example https://github.com/kstenerud/go-concise-encoding/blob/master... but I'll be simplifying the format some more). That way, we can run the same tests on all CE implementations instead of everyone coming up with their own. I'll move the test definitions to their own repo when they're done and then you can just submodule it.

I'm thinking that they should look more like:

    c1

Yes, that is exactly the aim of the binary format. It has a few basic concepts like being byte-oriented, 1-byte headers for most things, ULEB128 encoding for large values, same chunking mechanism for all arrays and string-likes, same "open/close" mechanism for all container types, etc.

The binary codec is VERY simple, and can be trivially implemented for an async-safe or otherwise constrained environment. In fact, I expect that many implementations will only build the binary codec, since you could just pass any recorded binary data through enctool [1] or whatever to see or manipulate its contents as a human. An embedded system would have no need to process the text format.

[1]https://github.com/kstenerud/enctool

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.