FreeMarker VS kubernetes

FreeMarker is a template engine, it allows to generate text output based on templates and dynamic data. It is similar to Mustache, Handlebars, Thymeleaf and other template engines. Templates are written in the FreeMarker Template Language (FTL) that supports conditional blocks, iterations, formatting, and many other capabilities.

Getting back to our two main technologies....we have implemented Keycloak as our Identification and Authorization Management system (IAM). However, as these things go, Keycloak has its own tech stack. One of the technologies, of course, is the language they used, which is Java. And being it is Java, they chose to use a templating engine called Freemarker.

The project I was working on was a website using Magnolia as their CMS. It uses the Freemarker templating engine under the hood. Essentially these are super-powered HTML files, which give you access to the CMS content. You can still use all of the HTML tags you want, including the

You can use Java for Backend and Frontend. A relative new kid on the block for Frontend is Qute. The general keyword you are searching for is Java Templating Engine. Specific examples would be Thymeleaf or FreeMarker. There are some framework, which offer a lot more than templating like Vaadin or Wicket. Some are just specifications like Jakarta Faces with some of their implementations MyFaces or Mojarra.

Keycloak uses FreeMaker to store and render templates. Read more about how Keycloak manages its themes in the official documentation.

For some component types, there is also the possibility to use a Freemarker template instead for more complex UI components. In this case, it will look like this:

From sing-up page to admin portal, you can customize pretty much any part of the UI using custom themes. Themes are developed using Freemarker Templates and it's all documented here.

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.

To learn more, you can start by exploring the official Kubernetes documentation.

With the containerized Node.js/Express API, I could run multiple containers, scaling to handle more traffic. Using a tool called minikube, we can easily spin up a local Kubernetes cluster to horizontally scale Docker containers. It was possible to keep one shared instance of the database, and many APIs were routed with an internal Kubernetes load balancer.

This package is widely used for powerful CLI builds, it is used for example for Kubernetes CLI and GitHub CLI, in addition to offering some cool features such as automatic completion of shell, automatic recognition of flags (the tags) , and you can use -h or -help for example, among other facilities.

We closely monitor Kubernetes and cloud providers' updates by following official changelogsand using RSS feeds, allowing us to anticipate potential issues and adapt our infrastructure proactively.

"You are holding it wrong", huh?

From the homepage https://kubernetes.io/:

"Kubernetes, also known as K8s, is an open-source system for automating deployment, scaling, and management of containerized applications."

Do you see "not recommended for smaller-scale applications" anywhere? Including on the entire home page? Looking for "small", "big" and "large" also yields nothing.

Open Source and Cloud Computing: A Match Made in Heaven The cloud is accelerating OSS adoption. Cloud-native technologies like Kubernetes [https://kubernetes.io/] and Istio [https://istio.io/], both open-source projects, are revolutionizing how applications are built and deployed across cloud platforms.

If you do kubectl explain deployment than (surprise!) you'll get a description for extensions/v1beta1. Because kubectl explain works the same way, just like kubectl get:

Through the Fast Forward program, we give free services and support to open source projects and the nonprofits that support them. We support many of the world’s top programming languages (like Python, Rust, Ruby, and the wonderful Scratch), foundational technologies (cURL, the Linux kernel, Kubernetes, OpenStreetMap), and projects that make the internet better and more fun for everyone (Inkscape, Mastodon, Electronic Frontier Foundation, Terms of Service; Didn’t Read).

In this project, you will understand and get hands on experience around the entire concept around CI/CD from applications perspective. To fully gain real expertise around this idea, it is best to see it in action across different programming languages and from the platform perspective too. From the application perspective, we will be focusing on PHP here; there are more projects ahead that are based on Java, Node.js, .Net and Python. By the time you start working on Terraform, Docker and Kubernetes projects, you will get to see the platform perspective of CI/CD in action.