Vagrant VS PostgreSQL

Vagrant

Take a look at Vagrant! https://www.vagrantup.com/ In my admittedly limited understanding I believe it offers closer to a nix like reproducable rather than repeatable deployments.

on the off chance one hasn't been tracking it, there were several "we don't need your stinking BuSL" projects when this drama first started:

https://github.com/opentofu#why-opentofu (Terraform)

https://github.com/openbao/openbao#readme (Vault)

and I know of several attempts at Vagrant <https://github.com/hashicorp/vagrant/forks> but I don't believe one of them has caught traction yet

There are also some who have talked about an "open Nomad" but since I don't play in that space I can't speak to it

It sounds like you're using Nix as a sort of configuration management solution. CM just isn't worth it for managing a single desktop IMO. It triples the effort for whenever you need to add or remove a package, as you must now add that also to your nix configuration. You're supposed to be able to make that back up in time saved restoring to the next machine, but inevitably the next machine will be different enough that you'll have to edit it all anyway. In the end I just got tired of trying to manage my own machine with infrastructure as code (though in fairness I was using puppet at the time not nix).

I keep a git repository with all my dot files in it[1]. This seems to work the best. It has a Windows folder as well, and I copy that out whenever I need to set up Windows.

A lot of people like using WSL but I hate how it hogs on my memory. Hyper-V is a terrible virtualization engine for consumer-grade use cases because it can't thin provision RAM. If I need to use docker, I will spin up a small Linux VM using vagrant[3] with Virtualbox[4] and put Docker on there. Vagrant is an extremely underrated tool in my opinion, particularly in a Windows context.

I use scoop for packages. Typically I will scoop install msys2 and then pin it so that it doesn't get blown away by the next upgrade.

Then I basically do all of my development inside of msys2. I can get most things running in there without virtualization. In my case that means sbcl and roswell for common lisp, senpai for irc, and tmux and nvim for sanity. Msys2 uses the pacman package manager and this is good enough.

All In all, I set up my Windows machine affresh after a while of not using it and it took me about 3 hours. Most of that time was just getting through upgrades though, I felt like it was pretty fast.

1: https://git.sr.ht/~skin/dotfiles

2: https://www.msys2.org/

3: https://www.vagrantup.com/

4: https://www.virtualbox.org/

Tools like Docker and Vagrant can be used to allow local environments to mimic production environments.

There's an open issue [1]. A scripting interface has since been added [2], and updated [3], so there's progress.

[1] https://github.com/hashicorp/vagrant/issues/12518

Someone should fork and maintain Vagrant with an MPL open source license:

https://github.com/hashicorp/vagrant

https://github.com/hashicorp/vagrant/blob/v2.3.7/CHANGELOG.m... ?

The changelog lists both improvements and bug fixes and there's even apparently some effort to port it away from ruby: https://github.com/hashicorp/vagrant/blob/v2.3.7/internal/cl...

PostgreSQL

The LMS Moodle Operator serves as a meta-operator, orchestrating the deployment and management of Moodle instances in Kubernetes. It handles the entire stack required to run Moodle, including components like Postgres, Keydb, NFS-Ganesha, and Moodle itself. Each of these components has its own Kubernetes Operator, ensuring seamless integration and management.

Another key feature of txtai is being able to quickly move from prototyping to production. This article will demonstrate how txtai can integrate with Postgres, a powerful, production-ready and open source object-relational database system. After txtai persists content to Postgres, we'll show it can be directly queried with SQL from any Postgres client

SQL (Structured Query Language) databases are relational databases. They organize data into tables with rows and columns, and they use SQL for querying and managing data. Examples include MySQL, PostgreSQL, and SQLite.

Node.js, MySQL and PostgreSQL servers installed on your machine

Each app’s front end is built with Qwik and uses Tailwind for styling. The server-side is powered by Qwik City (Qwik’s official meta-framework) and runs on Node.js hosted on a shared Linode VPS. The apps also use PM2 for process management and Caddy as a reverse proxy and SSL provisioner. The data is stored in a PostgreSQL database that also runs on a shared Linode VPS. The apps interact with the database using Drizzle, an Object-Relational Mapper (ORM) for JavaScript. The entire infrastructure for both apps is managed with Terraform using the Terraform Linode provider, which was new to me, but made provisioning and destroying infrastructure really fast and easy (once I learned how it all worked).

I've used MySQL for years. But recently, I found myself working PostgreSQL and simple things like dumping and restoring a database are different enough that I decided to document the process. It's straightforward enough once I knew how.

A running Rails application needs a database to connect to. You may already have your database of choice installed, but if not, I recommend PostgreSQL, or Postgres for short. On a Mac, probably the easiest way to install it is with Posrgres.app. Another option, the one I prefer, is to use Homebrew. With Homebrew installed, this command will install PostgreSQL version 16 along with libpq:

PostgreSQL