Mash is a Python based CI/CD pipeline for automated testing and publishing of public cloud images. Currently the production and development deployment for the package is inconsistent, slow and manual. This is a barrier to rapid development, deployment and testing. It also means the development workflow is different than production. This can lead to production issues which were not seen during development. In order to modernize the Mash workflow I plan to spend the week digging into a plethora of tools to first learn then build out a new workflow. The goal is to simplify deployment by choosing tools that provide consistency, modularity and repeatability. By leveraging the best tools available we can harden the code and accelerate the release cycle.

There are various home assistant solutions out there but all of them transfer your voice to some server for processing. This is a no-go for sane people although the technology is interesting and could be useful. There are various open source tools out there to achieve the same result but there is no turn key open source self hosted solution. The goal of this project is to implement a way to have a home assistant running locally - ideally with one command. The project that is closer to the desired result is Mycroft (https://mycroft.ai/). It is very easy to run the client side components using one docker command but their backend is running remotely. All the tools they use though are open source so it only needs one to do the work and package them in a nice little docker-compose file (https://mycroft-ai.gitbook.io/docs/about-mycroft-ai/faq#can-mycroft-run-completely-offline-can-i-self-host-everything).

Zero-ish downtime deploy on da cheap!

This project aims to get a 0-ish downtime deployments (very easily achievable with Kubernetes) just using: