edn VS kubernetes

> was utterly surprised how no one ever apparently has thought to create a configuration/templating system that's basically a fancy library on top of Scheme.

There's Clojure's extensible data notation: https://github.com/edn-format/edn

A thin language layer around edn/datalog, the query language

EDN (Extensible Data Notation) is a subset of Clojure: https://github.com/edn-format/edn

It is:

- Streamable

- Extensible

- Whitespace-insensitive, but there are formatting conventions for readability

To begin with, EDN is somewhat like the JSON of Clojure. And regarding the code is data/data is code nature of Clojure, it is Clojure. It doesn't have some of the vagaries of JSON, and it is also extensible.

Alien is not a reason something is bad, just that's it's unusual. JSON was a bit alien when it first arrived as well, as everyone was used to XML at the time.

`{num 5, val 4}` looks fine to me, but we can do even better! We already know objects/maps are always in pairs, so we don't really need that comma either. Just do `{num 5 val 4}` and we save yet another unnecessary characters.

Of course, I didn't come up with this format myself, what I actually want JSON to be is EDN (https://github.com/edn-format/edn) which is a standalone format but also directly used in Clojure, so it already exists inside a programming language and works very well. There keys are strings though, so you example would end up being `{"num" 5 "val" 5 "person" var}`, where commas are optional.

I just checked out the spec, and it gets pretty ugly in the Table section. A lot of the json examples are both shorter and IMO more precise. Stuff that’s not allowed with [table] is allowed with [[table]], and it’s confusing to understand what level of depth I’m at.

I’ll take edn over any of “em. https://github.com/edn-format/edn

As XT is written in Clojure and it natively supports Clojure’s data types, we were not satisfied with available JSON types and decided to give EDN a try - that way we would have way more supported types:

Compare the nightmare that is pickling with how simple it is to serialize pure data with edn in clojure. What ends up happening is people passing around JSONs or whatever and writing parsing/encoding code at each end, which makes things unnecessarily more complex, and dangerous, and error prone, and boring, etc...

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.

The single most important development in hosting since the invention of EC2 is defined by its own 3-letter acronym: k8s. Kubernetes has won the “container orchestrator” space, becoming the default way that teams across industries are managing their compute nodes and scheduling their workloads, from data pipelines to web services.