toxiproxy VS Juju

Checkout also shopify's awesome tool called toxiproxy: https://github.com/Shopify/toxiproxy

It turns out to be also a very good way to test a networking library by implementing it. Since your stack needs to be able to basically handle most adverse events properly.

The idea behind 'chaos engineering' is cool.

I use this to simulate delays between various local services:

https://github.com/Shopify/toxiproxy

If you have Docker all you need is a few terminal commands

Idk about firewall level, but application level I’d recommend https://github.com/Shopify/toxiproxy

That's why I usually recommend anybody that develops network critical apps to test their app with something like toxiproxy and purposfully mess with their connections and simulate network issues.

We use this thing. https://github.com/Shopify/toxiproxy I am not sure that it supports windows, but you can install it to the Linux machine and route your application under the test to that proxy.

On the same vibes as https://github.com/Shopify/toxiproxy

https://github.com/Shopify/toxiproxy is a perfect solution for that. I used it quite successfully years ago and it looks like it's still pretty active.

Looking at the toxiproxy you mentioned, it seems like it should do what you want though? TLS is generally over TCP anyway, so it should still be able to throttle those connections - it just wont understand the encryption. I also saw a pull request for having it act as a TLS man-in-the-middle proxy: https://github.com/Shopify/toxiproxy/pull/270

Basically juju is used to deploy microservices, and other stuff too: https://juju.is/

Juju https://juju.is/

https://juju.is/

Each app is packaged in a charm which seems to be a yaml declaring inputs, dependencies and other meta data and optional python code that can respond to certain lifecycle hooks

https://discourse.charmhub.io/t/implementing-relations/1051

   name: my-node-app

I am currently working myself through setting up our new Research GPU-Cluster where we have "sort of" managed to deploy MAAS to manage all the servers more efficiently, and on top of MAAS then use Juju to deploy the further components of the cluster. The components here are

Kubernetes Custom Resources were created to allow the Kubernetes API to be extended for domain-specific logic, by defining new resource types and controllers. OSS frameworks like operator-sdk, kubebuilder and juju were created to simplify the creation of custom resources and their controllers. Tools built with these frameworks came to be known as Operators.

Depending on what you're trying to accomplish, Juju and MAAS, if not just automate with preseed for custom desktops.

At Canonical I work on two open-source projects written in Go: Juju, a large cloud-based application deployment tool, and Pebble, a small Linux service manager. Both include CLI clients and API-based server daemons. Juju in particular is a large distributed system.

The new Portainer charm allows users of Canonical’s Charmed Kubernetes distribution to automatically install and integrate Portainer Business as part of the Kubernetes cluster deployment process, using Juju, the Charmed Operator framework.