kind
kubernetes
Our great sponsors
kind | kubernetes | |
---|---|---|
182 | 651 | |
12,663 | 106,117 | |
1.7% | 1.2% | |
8.8 | 10.0 | |
4 days ago | 1 day ago | |
Go | Go | |
Apache License 2.0 | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
kind
-
How to distribute workloads using Open Cluster Management
To get started, you'll need to install clusteradm and kubectl and start up three Kubernetes clusters. To simplify cluster administration, this article starts up three kind clusters with the following names and purposes:
-
15 Options To Build A Kubernetes Playground (with Pros and Cons)
Kind: is a tool for running local Kubernetes clusters using Docker container "nodes." It was primarily designed for testing Kubernetes itself but can also be used for local development or continuous integration.
-
Exploring OpenShift with CRC
Fortunately, just as projects like kind and Minikube enable developers to spin up a local Kubernetes environment in no time, CRC, also known as OpenShift Local and a recursive acronym for "CRC - Runs Containers", offers developers a local OpenShift environment by means of a pre-configured VM similar to how Minikube works under the hood.
-
K3s Traefik Ingress - configured for your homelab!
I recently purchased a used Lenovo M900 Think Centre (i7 with 32GB RAM) from eBay to expand my mini-homelab, which was just a single Synology DS218+ plugged into my ISP's router (yuck!). Since I've been spending a big chunk of time at work playing around with Kubernetes, I figured that I'd put my skills to the test and run a k3s node on the new server. While I was familiar with k3s before starting this project, I'd never actually run it before, opting for tools like kind (and minikube before that) to run small test clusters for my local development work.
-
Mykube - simple cli for single node K8S creatiom
Features compared to https://kind.sigs.k8s.io/
-
Hacking in kind (Kubernetes in Docker)
Kind allows you to run a Kubernetes cluster inside Docker. This is incredibly useful for developing Helm charts, Operators, or even just testing out different k8s features in a safe way.
-
K3s – Lightweight Kubernetes
If you're just messing around, just use kind (https://kind.sigs.k8s.io) or minikube if you want VMs (https://minikube.sigs.k8s.io). Both work on ARM-based platforms.
You can also use k3s; it's hella easy to get started with and it works great.
-
Two approaches to make your APIs more secure
We'll install APIClarity into a Kubernetes cluster to test our API documentation. We're using a Kind cluster for demonstration purposes. Of course, if you have another Kubernetes cluster up and running elsewhere, all steps also work there.
-
observing logs from Kubernetes pods without headaches
yes I know there is lens, but it does not allow me to see logs of multiple pods at same time and what is even more important it is not friendly for ephemeral clusters - in my case with help of kind I am recreating whole cluster each time from scratch
-
We moved our Cloud operations to a Kubernetes Operator
Unit tests were written against an in-memory Kubernetes API server using the controller-runtime/pkg/envtest library. Envtest allowed us to iterate quickly since we could run tests against a fresh API cluster that started up in around 5 seconds instead of having to spin up a new cluster every time we wanted to run a test suite. Even existing micro-cluster tools like Kind could not get us that level of performance. Since envtest is also not packaged with any controllers, we could also set our test cluster to a specific state and be sure that this state would not be modified unless we explicitly did so in our test code. This allowed us to fully test specific edge-cases without having to worry about control plane-level controllers modifying various objects out from underneath us.
kubernetes
-
Open Source Ascendant: The Transformation of Software Development in 2024
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.
-
Open source at Fastly is getting opener
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).
-
Experience Continuous Integration with Jenkins | Ansible | Artifactory | SonarQube | PHP
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 2024 Web Hosting Report
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.
-
The Road To Kubernetes: How Older Technologies Add Up
Kubernetes was first released on September 9, 2014. This release timeline is part of what helped it gain a foothold over Docker Swarm. It was an open source version of an internal Google project. Features of container orchestration were presented in a more modular fashion along with scaling functionality. You can chose how your networking stack works, your load balancing, container runtime, and filesystem interfaces. Availability of an API allowed for more programmatic interactions with orchestration, making it tie in very well with CI/CD solutions. However, the big issue it has is complexity of setup. Putting together a Kubernetes cluster with basic functionality is certainly no easy feat.
-
Deploying flask app to Kubernetes using Minikube
Kubernetes manages the deployment, scaling, and operation of containerized applications across a cluster of machines. Kubernetes relies on tools such as container runtimes like Docker, to run the containers.
-
Oasis – a small, statically-linked Linux system
If you go by version number and anything < 1.0 being not production ready, I recommend avoiding reading any of the dependency files for large software products which are often used in produciton, they might cause you some concern...
https://github.com/kubernetes/kubernetes/blob/master/go.mod for one obvious example.
-
Fun with Avatars: Containerize the app for deployment & distribution | Part. 2
Container Orchestration tools: These are used to automate the deployment, scaling, monitoring, and management of containerized applications. These tools simplify the complexities of managing and coordinating containers across a cluster of machines. They include Kubernetes, Docker Swarm, Amazon ECS, Microsoft AKS, Google Kubernetes Engine (GKE), etc.
-
Exploring OpenShift with CRC
OpenShift Container Platform (OCP), otherwise known as just OpenShift, is a comprehensive, feature-complete enterprise PaaS offering by Red Hat built on top of Kubernetes, available both as a fully managed service on popular public cloud platforms such as AWS (ROSA) and as an internal developer platform (IDP) to be deployed on-premises on existing private cloud infrastructure, as VMs or on bare metal.
-
Why bad scientific code beats code following "best practices"
There are some things that should be in one long function (or method).
Consider dealing with the output of a (lexical) tokeniser. It is much easier to maintain a massive switch statement (or a bunch of ifs/elseifs) to handle each token, with calls to other functions to do the actual processing, such that each case is just a token and a function call. Grouping them in some way not required by the code is an illusory "gain": it hides the complexity of the actual function in a bunch of files you don't look at, when this is not a natural abstraction of the problem at all and when those files introduce extra layers of flow control where tricky bugs can hide. Or see the "PLEASE DO NOT ATTEMPT TO SIMPLIFY THIS CODE" comment from the Kubernetes source[0]. A 300 line function that does one thing and which cannot be usefully divided into smaller units is more maintainable than any alternative. Attempting to break it up will make it worse.
That being said, I agree that nearly all 300 line functions in the wild are not like this.
[0] https://github.com/kubernetes/kubernetes/blob/ec2e767e593953...
What are some alternatives?
Apache ZooKeeper - Apache ZooKeeper
minikube - Run Kubernetes locally
bosun - Time Series Alerting Framework
k3d - Little helper to run CNCF's k3s in Docker
Rundeck - Enable Self-Service Operations: Give specific users access to your existing tools, services, and scripts
lima - Linux virtual machines, with a focus on running containers
kine - Run Kubernetes on MySQL, Postgres, sqlite, dqlite, not etcd.
BOSH - Cloud Foundry BOSH is an open source tool chain for release engineering, deployment and lifecycle management of large scale distributed services.
vcluster - vCluster - Create fully functional virtual Kubernetes clusters - Each vcluster runs inside a namespace of the underlying k8s cluster. It's cheaper than creating separate full-blown clusters and it offers better multi-tenancy and isolation than regular namespaces.
colima - Container runtimes on macOS (and Linux) with minimal setup
Juju - Orchestration engine that enables the deployment, integration and lifecycle management of applications at any scale, on any infrastructure (Kubernetes or otherwise).
SaltStack - Software to automate the management and configuration of any infrastructure or application at scale. Get access to the Salt software package repository here: