Huginn – Build agents that monitor and act on your behalf
github.com
github.com
https://news.ycombinator.com/item?id=7585605 (2 years ago)
https://news.ycombinator.com/item?id=5377651 (3 years ago)
- Bipio @ https://github.com/bipio-server/bipio
Is/are there any such framework/s built with/in Python too?
[1] disclosure: I'm one of the core dev [2] http://ramses.readthedocs.org [3] https://elastalert.readthedocs.org
What an awkward regex! :)
Feature wise, I would say should start with everything we have in Huginn.
Glad to see someone creating a manager for this kind of thing.
I'm a software engineer at a small startup that makes this open source engine that automates environments orchestration using containers.
We created a super easy way to quickly (and safely) run applications such as Huginn from source code locally on your own workstation.
It takes little more than just a click.
Go to this fork of the project and click the "Run Project" button:
https://github.com/run-project/huginn#running-locally
The only addition made to the original project is a manifest file about the OS, languages, databases etc. required by the project.
Afterwards, if you want to deploy to DigitalOcean from your desktop, you can do it in very few steps following these instructions:
https://github.com/run-project/huginn#deploying-to-digitaloc...
It would be great to get some feedback about it. Hope it helps!
Thanks.
Is this an alternative to Vagrant?
Why wouldn't I use Docker instead of azk?
Instead of dealing with individual virtual machines one by one as you'd do with Vagrant, you'll just write a simple system-level manifest file (Azkfile) listing the environment's elements and the relationships between them and "hit play".
azk builds the environment for you with little intervention, in a short amount of time and you can easily replicate the results in other machines using that same Azkfile.
With azk, automation does NOT come at the cost of opacity. You can always look "under the hood" and see what's going on.
Today, azk employs Docker, but frankly, we could use any other equivalent solution (as we are currently testing).
Compared to Docker Compose, we can list the following advantages:
- Its manifest file (a DSL in Javascript) is more verbose and has a greater toolset [0];
- You can persist content from inside the container way better than simply mounting volumes using docker compose [1];
- For now, it relies on VirtualBox (usign debian2docker) but it has a built-in function [2] to sync folders into the container using rsync (significantly increasing performance for file sharing). You can still use VirtualBox Shared Folders if you want to;
- Its built-in DNS server makes you don't worry about port mapping and docker IP issues. You can access your local app running with azk by simply accessing a custom address, like: my-app.dev.azk.io.
We like to think of azk as the YouTube to Docker's Adobe Flash Video.
We've built a gallery [3] with some projects where you can have a first experience with azk by running them. If you get interest, you can learn how to write Azkfiles to your projects by accessing [0].
This three and half minutes video shows azk in use [4].
[0] http://docs.azk.io/en/azkfilejs
[1] http://docs.azk.io/en/reference/azkfilejs/mounts.html#persis...
[2] http://docs.azk.io/en/reference/azkfilejs/mounts.html#sync
When we created azk, we had developers in mind.
Solutions such as those or the `Deploy with Heroku` button are cool, but they don't give developers the opportunity to just fiddle with the code or even just check how the application looks like running locally before deployment.
So we tried to expand on those solutions by adding this capability on it (and you can always easily deploy to DigitalOcean with azk).
Another thing I'd like to know when signing up to a service like this is if and how I can get my data with me if I decide to migrate to a self-hosted version for example.
I don't know how you measured that, but Linux will use all of your memory all of the time with various caches.
Seems interesting but the metaphors are rather different.
They are a bit different. However, with many of the node-red-contrib modules, I can do things like "watch twitter for certain #tags, send them to IRC along with a semantic analysis. Also log to MongoDB. And any @ send to my email every sunup."
The basic functionality of the core nodes is already impressive, but the contrib is where Node-Red shines.
https://github.com/cantino/huginn/graphs/contributors https://github.com/node-red/node-red/graphs/contributors
So for now, if your usage is the same as mine. Perhaps huginn would work better.
I do like how node-red have that drag and drop interface though.