Capistrano VS PostgreSQL

If you don't want to go down the NFS share route then Capistrano is a useful tool if you're willing to write a little bit of ruby. It comes with some built in goodies like rollbacks. It's an oldie (pre-dockerize everything), but still useful.

https://github.com/capistrano/capistrano

You can start by deploying from your machine to simultaneously get it deploying across all your servers, then I'd consider having a CI/CD pipeline take over and run Capistrano for you.

- Integrate automation deployment: [capistrano](https://github.com/capistrano/capistrano)

Integrate automation deployment: capistrano

The deployment process generally includes making the new version available, directing traffic from the old to the new version, and stopping the old versions. Capistrano has been doing this since 2006. However, what makes Kubernetes deployments better is the minimum number of pods required, and its rollout strategy minimizes or eliminates downtime. For example, a rolling update strategy can ensure new pods gradually replace old pods with configs like maxSurge and maxUnavailable. Because this is done in a declarative way, as a user or operator, you only need to ask Kubernetes to apply a given deployment and Kubernetes does the rest. Next up is the Kubernetes config map.

[1] https://github.com/capistrano/capistrano

Capistrano

What I had considered was writing a deployment script where upon successful build in a separate folder, it'd swap out the deployed folder, similar to how Capistrano works. It has a "current" folder and it'll build in a temporary folder and then replace the symlink to a newer build.

capistrano with plugins for deployment

deployer is a deployment tool written in PHP. It comes with "Zero Downtime Deployments" out of the box and can be extended by writing simple PHP code. (capistrano would be the equivalent in the Ruby world).

Capistrano, if you like Ruby.

Data Handling: Utilizes Windmill for data pipelines, with a primary database powered by PostgreSQL. Auxiliary data storage is handled by MongoDB, with Redis for caching to optimize performance

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: