grpc-web VS rupy

* Additionally, client can stream data to the backend server (if bidirectional GRPC streams are used). I.e. client sends WebSocket messages, those will be transformed to GRPC messages by WebSocket server and delivered to the application backend.

As a result we have a system which allows to quickly create individual streams by using strict GRPC contract but terminating connections over WebSocket transport. So it works well in web browsers. After that no need to write WebSocket protocol, client implementation, handle WebSocket connection. This all will be solved by a suggested WebSocket server and its client SDKs.

The mechanics is similar to Websocketd (https://github.com/joewalnes/websocketd), but instead of creating OS processes we create GRPC streams. The difference from grpc-web (https://github.com/grpc/grpc-web) is that we provide streaming capabilities but not exposing GRPC contract to the client - just allowing to stream any data as payload (both binary and text) with some wrappers from our client SDKs side for managing subscriptions. I.e. it's not native GRPC streams on the client side - we expose just Connection/Subscription object to stream in both directions. GRPC streams used only for communication between WebSocket server and backend. To mention - grpc-web does not support all kinds of streaming now (https://github.com/grpc/grpc-web#streaming-support) while proposed solution can. This all should provide a cross-platform way to quickly write streaming apps due to client SDKs and language-agnostic nature of GRPC.

I personally see both pros and cons in this scheme (without concentrating on both too much here to keep the question short). I spent some time thinking about this myself, already have some working prototypes – but turned out need more opinions before moving forward with the idea and releasing this, kinda lost in doubts.

My main question - whether this seems interesting for someone here? Do you find this useful and see practical value?

By default, web browsers do not support gRPC, but we will use gRPC-web to make it possible.

You just have to use a library implementation for JavaScript https://github.com/grpc/grpc-web

TypeScript support remains an experimental feature of gRPC.

The gRPC-Web protocol supports HTTP/1 and can be used from a browser.

-- grpc-web

gRPC is mainly used in server-to-server communication, but it can also be used in client-to-server communication. gRPC-web is a gRPC implementation for web browsers. It is a JavaScript library that allows you to call gRPC services from a web browser. It supports Unary and Streaming Server API calls.

Since we're using Envoy, there's one more neat trick that we can employ. It turns out that Envoy also support gRPC-Web out of the box, a JavaScript client designed to support gRPC communication from the browser! That means that we can send gRPC messages over HTTP/1.1 as base64 encoded strings or as binary protobufs. Messages will be sent through our proxy and on to our backend service. The advantage of this is smaller and more efficient wire communication which should lead to better performance.

protoc-gen-grpc-web — a plugin that allows our front end to communicate with the backend using gRPC calls. A separate blog post on this coming up in the future.

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.