docker VS PostgreSQL

Deploying AI models into production requires tools that can package applications and manage them at scale. Docker simplifies the deployment of AI applications by containerizing them, ensuring that the application runs smoothly in any environment. Kubernetes, an orchestration system for Docker containers, allows for the automated deployment, scaling, and management of containerized applications, essential for AI applications that need to scale across multiple servers or cloud environments.

Linux Mint with Cinnamon: https://www.linuxmint.com/ as far as desktop OSes go it's familiar (Ubuntu without snaps by default), whereas the UI feels both snappy, doesn't use too much resources and is actually pretty to look at.

MobaXTerm: https://mobaxterm.mobatek.net/ this one is a bit more Windows centric but I ended up paying for it and replaced mRemoteNg and PuTTY with it, it's even better than Remmina or whatever Linux has to offer - you can manage SSH/RDP/VNC/... sessions, input across multiple sessions side by side and it just simplifies things a lot (jump host support, a port forwarding too and so much more).

GitKraken: https://www.gitkraken.com/ also a piece of software that I paid for, this one actually makes using Git pleasant, feels better to use than SourceTree and Git Cola (even though that latter is wonderfully lightweight, too) and honestly I prefer that to the CLI nowadays.

Kanboard: https://kanboard.org/ is a lightweight Kanban project management tool, it might not have every feature under the sun but it's the most snappy project management tool I've ever used, looks simple and runs well. I honestly love it, what a nice thing to have.

Most modern text editors and IDEs: I personally pay for JetBrains IDEs but also like Visual Studio Code as a text editor and both have helped me immensely, they're reasonably performant when you have the RAM, look nice, often give you suggestions about how to improve your code and also have a plethora of plugins in their ecosystems. Nowadays I unapologetically use LLMs as well and overall it feels like I have these great tools and cool autocomplete (that is sometimes a bit silly and wrong) at my disposal, that makes me happy.

Kdenlive: https://kdenlive.org/ imagine if there was a successor to Windows Movie Maker, though something that gets most of the important stuff out of Sony Vegas, except is also completely free and works on most platforms. Kdenlive is all of that and also somehow quite pleasant to use, I actually prefer it to DaVinci resolve. There is a bit of a learning curve to any piece of software like this, but everything mostly makes sense in this one.

Gitea: https://about.gitea.com/ I still use this for my personal Git repositories and integrating with CI systems and it's lightweight, looks good and just feels pleasant to use. Previously I self-hosted GitLab and constantly ran into resource exhaustion as well as doubts about the next update is going to corrupt all of my data and break (it did), so now I use Gitea instead.

Drone CI: https://www.drone.io/ a container native CI solution that I can also self host. It's container oriented, integrates with Gitea nicely, is similarly nice to GitLab CI and doesn't cause me headaches like Jenkins would.

Docker: https://www.docker.com/ yes, even Docker desktop. It just makes working with containers really pleasant and predictable, even when something like Podman also exists (and also is great). I don't know, I feel like Docker really saved me from having brittle legacy environments, even self-contained containers with health checks and resource limits with still the same brittle code inside of those make me feel way more safe.

Note: Before running your application in the next step, make sure you have Docker installed and running. It's required to locally run Encore applications with databases.

Developing WordPress plugins and themes often requires a reliable development environment. Current we have good solutions as wp-env from Autommatic, Local WP from WP Engine, Docker, XAMPP (for old ones) and so on. All this can be good suits for a development environment, specially Local WP that is probably the easiest one to get up and running and wp-env that leverages Docker as a development environment in a very easy way to use.

Docker, an open-source development platform, provides containerization technology for building and packaging applications along with their dependencies into portable images.

With each app containerized with Docker, this allows it to be run on any other developer's machine also running Docker. Although I had automated deployments to Heroku without this, I decided to upload each service to a container registry.

Docker

Today we are going to see all the power that a CLI (Command line interface) can bring to development, a CLI can help us perform tasks more effectively and lightly through commands via terminal, without needing an interface. For example, git and Docker, we practically use their CLI all the time, when we execute a git commit -m "commit message" or docker ps -a we are using a CLI. I'm going to leave an article that details what a CLI is.

Docker (required): Understanding Docker is crucial for deploying software in containers, making your project portable and scalable. I use it for start Folo server.

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