Apache NetBeans VS kubernetes

This page doesn't give any details about what's changed in this release.

More informative page: https://github.com/apache/netbeans/releases/tag/20

The IDE we use on this course is called NetBeans, and we use it with the Test My Code plugin.

I believe Netbeans is the preferred IDE for the mooc. There is a plugin for IntelliJ, but I've heard mixed reviews.

> For the most part, Eclipse has fallen into obscurity.

I guess it depends on the locale/company/environment?

In most conferences, online videos, as well as among the people I know personally, JetBrains IDEs (IntelliJ IDEA for Java) seem to reign supreme: https://www.jetbrains.com/idea/

They have a community version, personally I pay for the Ultimate package of all the tools. They're slightly sluggish, want a lot of RAM, but the actual development experience and features make up for that.

I know that Eclipse is sometimes used more in an educational setting, however there are also both some specialized tools, as well as customized versions for something like working with Spring in the industry: https://spring.io/tools

In my experience, the idea behind the IDE is nice (a platform that you can install whatever you want on, entire language support packages, or specialized tool packages), but the execution falls short - sometimes it's unstable, other times it works slow and so on. That said, it's passable.

I would say that personally I'd almost prefer NetBeans to Eclipse, even after it was given over to the Apache Foundation, which have released a few versions since: https://netbeans.apache.org/

It seems to do less than either Eclipse or IntelliJ IDEA do, but for general purpose Java editing and limited work with other stacks (PHP, webdev stuff, some C/C++) it is good and pleasant to use. However, if you have projects that get close to half a million lines of code, it does just kind of break and gets way slower than the alternatives. It still somehow feels more coherent than Eclipse to me, would pick it if IntelliJ IDEA didn't exist.

Some also try doing something like using Visual Studio Code with a Java plugin: https://code.visualstudio.com/docs/languages/java

That said, I only used that briefly when I needed something lightweight for a netbook of mine, the experience was somewhat underwhelming. The autocomplete or refactoring wasn't as good as IntelliJ IDEA and just felt a little bit tacked on. Then again, that was a while ago, I don't doubt that progress is being made.

(free) Apache NetBeans is there from ages, and one person on my team still uses it for PHP/web stuff (including the use of xdebug with it) because you know, it works. Some of us care about *what* gets into the repository, not *how* it gets done, as long you're productive.

Existem outras IDEs igualmente famosas: Eclipse IDE e NetBeans.

1. NetBeans

Nobody mentioned (wonder why), but 10 years ago I used work in NetBeans. I thought it was fantastic and I can see it is still being developed.

In the field of software development, efficiency and agility are always sought after. In the era of cloud-native apps, traditional deployment techniques—which are frequently laborious and prone to errors—are starting to become obstacles. This is when Kubernetes and GitOps come in handy.

Are you looking for a hassle-free way to deploy Moodle™ Learning Management Systems (LMS) on Kubernetes? Look no further! Krestomatio presents the LMS Moodle Operator, an open-source Kubernetes Operator designed to simplify the deployment and management of Moodle instances on Kubernetes clusters. Let's dive into what makes this tool a great choice for Moodle administrators and developers alike.

Securing access to your Kubernetes clusters is crucial as inadequate security measures can lead to unauthorized access and potential data breaches. However, navigating the complexities of Kubernetes access security, especially when setting up strong authentication, authorization, and network policies, can be challenging.

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.