gokrazy
rupy
gokrazy | rupy | |
---|---|---|
19 | 31 | |
3,153 | 136 | |
0.3% | - | |
7.7 | 1.1 | |
18 days ago | about 1 year ago | |
Go | Java | |
BSD 3-clause "New" or "Revised" License | - |
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gokrazy
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Considerations for a long-running Raspberry Pi
Switching to gokrazy[0] was the best thing I did for my Raspberry Pi uptimes. I think a lot of that is because it defaults to using read-only partitions so the common issue of SD cards falling over when you run apt upgrade no longer happens.
But I also think that gokrazy's simplicity and design helps it be just a solid, reliable foundation to build on top of.
[0]: https://gokrazy.org/
- Gokrazy – Go Appliances
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Easylkb: Easy Linux Kernel Builder
The idea there sounds a lot like https://gokrazy.org/, which builds a minimal go userland, wrapping one or more user provided go applications, and bundles in a linux kernel.
Targets mostly at single board computers, and I think it downloads pre-built kernels (and bootloaters if needed), rather than trying to build them directly, since getting a working cross compilation toolchain set up and plumbed into the kernel compilation process is still a pain.
I've personally only used yocto/open-embedded for that which does nicely handle building the cross-compilation toolchain, kernel image, and modules. But it is kinda overkill for that task, being designed to build a whole userland too.
- An Overview of Nix in Practice
- Gokrazy Go (Golang) Appliances
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Writing an OS in Go: The Bootloader
reminds me of https://github.com/gokrazy/gokrazy which does similar things.
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When is go not a good choice?
https://gokrazy.org/ would like a word
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Userspace isn't slow, some kernel interfaces are
Fun! We have support for running on gokrazy (https://gokrazy.org/) already, and that's probably where Unikernel Linux is more applicable for us, for when people just want a "Tailscale appliance" image.
I'll email you.
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go-rampart: a golang package to detect overlapping periods
gokrazy exists! https://github.com/gokrazy/gokrazy
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Can you build your own user space on top of the Linux kernel?
https://github.com/gokrazy/gokrazy for one example
rupy
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Considerations for a long-running Raspberry Pi
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!
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What Kind of Asynchronous Is Right for You?
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.
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An unknown Swedish startup’s €3B bid to build a green rival to AWS
The hardware is peaking.
So software is where you can make the difference: http://host.rupy.se
- Sandstorm: Open-source platform for self-hosting web app
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You Want Modules, Not Microservices
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.
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I wish my web server were in the corner of my room
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?
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Ask HN: Free and open source distributed database written in C++ or C
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
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Dokku – Free Heroku Alternative
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!
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Server-Sent Events: the alternative to WebSockets you should be using
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.
- Jodd – The Unbearable Lightness of Java
What are some alternatives?
buildroot - Buildroot, making embedded Linux easy. Note that this is not the official repository, but only a mirror. The official Git repository is at http://git.buildroot.net/buildroot/. Do not open issues or file pull requests here.
huproxy
go-jtagenum - JTAG enumeration tool written in Go. A port of https://github.com/cyphunk/JTAGenum enhanced with https://github.com/grandideastudio/jtagulator improved implementation.
cmdg - Command line Gmail client
xbvr - Tool to organize and stream your VR porn library
Nullboard - Nullboard is a minimalist kanban board, focused on compactness and readability.
tamago - TamaGo - ARM/RISC-V bare metal Go
cakephp-swagger-bake - Automatically generate OpenAPI, Swagger, and Redoc documentation from your existing CakePHP code.
qt - Qt binding for Go (Golang) with support for Windows / macOS / Linux / FreeBSD / Android / iOS / Sailfish OS / Raspberry Pi / AsteroidOS / Ubuntu Touch / JavaScript / WebAssembly
dbmate - :rocket: A lightweight, framework-agnostic database migration tool.
nixos-anywhere - install nixos everywhere via ssh [maintainer=@numtide]
Aerospike - Aerospike Database Server – flash-optimized, in-memory, nosql database