leapp VS rupy

Summary:

Do you find yourself overwhelmed with work, requests, or complaints and in need of assistance to alleviate the pressure, enhance communication, facilitate organization, prioritize tasks, and foster greater trust and transparency?

Alternatively, I can work as a full stack developer.

AWS Community builder, AWS User group Leader, public speaker (https://www.youtube.com/watch?v=qdu58NAQfU0&t=271s)

Or perhaps you need both? =)

I have 4+ years of experience as a product manager and 8 in product development (before pm: agile coach, UX designer, and developer).

I've been the co-founder of the open-core company behind the OSS project Leapp (https://github.com/Noovolari/leapp)

Please feel free to reach out.

You can switch to saml2aws using the browser method instead of the Okta method and it will continue to work after the upgrade. There is also a really neat GUI tool to manage your session tokens that also works. https://www.leapp.cloud

Take a try to Leapp: https://github.com/Noovolari/leapp

Hello everyone, I'm the maintainer of an open-source DeveloperTool (https://github.com/Noovolari/leapp)

With a heuristic of 7000 users daily, I started feeling the need to have more information on how Users are using the project to improve it.

Is it the right thing to do to create a better Developer Experience and gain feedback for the end users?

On a side:

- For all your employees I can advice you Leapp as open-source project (https://github.com/Noovolari/leapp). It solve mayor of the problem listed here:

I am looking to manage Leapp (https://www.leapp.cloud/) from the StreamDeck. Leapp allows you to manage and switch between different Cloud Accounts (AWS, Azure, etc). Leapp has a command line interface which I could automate with a StreamDeck plugin. Unfortunately it looks like the only official SDK is the sandboxed JavaScript one. This means I cannot automate command line tools with it.

If you’re wondering if there is a tool that allows you to stop thinking about AWS credentials and where to store them in the right way, give a look at Leapp! It takes the responsibility of storing long-term credentials in the system vault, generating/refreshing short-term credentials, and placing them in the right place for the clients to use them.

Still, there is an elementary problem that we need to address, and it’s more on the operational side of things. Once we secured and implemented a tremendous multi-account strategy, how do people access AWS accounts? It turns out there is a fantastic open-source tool that lets you handle that with no effort, and its name is Leapp.

When you have to configure access to multiple AWS accounts using the Assume Role access pattern, it becomes difficult to get rid of all the Named Profiles configuration data and relationships. When you’ve to deal with a complex access scenario, tools like Leapp (https://www.leapp.cloud) come to the rescue! Leapp avoids you to specify relationships between Named Profiles in the config file, as the access methods are stored in the tool-specific configuration file.

Leapp Github repository

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.