Universal-Kubernetes-Helm-Charts
kind
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Universal-Kubernetes-Helm-Charts | kind | |
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17 | 182 | |
101 | 12,767 | |
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6.7 | 8.9 | |
20 days ago | 6 days ago | |
Smarty | Go | |
MIT License | Apache License 2.0 |
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Universal-Kubernetes-Helm-Charts
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Dedpulication standards of Helm Charts values file for a global chart with subcharts for our app. What's the right way to only need to specify a value once?
I would point you to what I call the "Universal Helm Charts" and some examples of how to use them.
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Monitoring many cluster k8s
Shameless Plug: Here's one of my dashboards I made for Ingress-Nginx, which is my recommended border router/gateway into all the services. It adds deep robust metrics and configurability, and if you've got years of experience with Nginx also, it allows you rich complex customization via nginx's configuration structure via kubernetes annotations. Besides that I have open-source helm charts which are easy to use, boilerplates showing how to use them, a volume autoscaler to automatically resize your disks as they get full, and a blog where I share various of my experience which is a companion blog to my upcoming book of the same name. Hope this helps! Feel free to ask if you have any further questions.
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Best way of managing Helm?
You may want to check out some other of my Helm Boilerplates to explain and highlight how using subcharts works. This is a companion repo to my upcoming DevOps + Kubernetes book. You also might like to check out my set of open-source universal helm charts which are published in a helm registry right now that you can leverage and has many industry best-practices built into it, such as anti-affinity rules, pod disruption budgets, horizontal pod autoscaling, ingress, service support, etc.
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How do you guys on Mac M1's get around the annoying port forwarding issues with k8s + docker?
References: I use docker and Kubernetes daily. I currently manage numerous clusters and maintain pipelines for hundreds of microservices as I type this. I've been converting microservices into Docker images for companies hundreds if not thousands of times by now over the last bunches of years. I am also an avid and passionate open-source evangelist and Kubernetes/DevOps consultant. I author some Kubernetes controllers such as the Volume Autoscaler and have a set of Open Source Helm Charts and I love to contribute code/fixes wherever I run into issues.
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StatelessSet Resource Type ?
If it helps at all I have some universal helm charts that have a template for easily deploying your application as a deployment or statefulset. You will notice I don’t even have a daemonset chart because it doesn’t make sense to. https://github.com/DevOps-Nirvana/Universal-Kubernetes-Helm-Charts
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Helm makes it overly complex, or is it just me?
See: Open-Source Universal Helm Charts See: Boilerplates of using Open-Source Helm Charts (as a sub-chart)
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The Helmet is a Helm Library Chart that defines many chart templates like Deployment, Service, Ingress, etc which can used in other application charts.
Helm charts - https://github.com/DevOps-Nirvana/Universal-Kubernetes-Helm-Charts Example using helm charts as sub charts - https://github.com/DevOps-Nirvana/Helm-Chart-Boilerplates/tree/master/boilerplate-echoserver
- How do you guys manage your deployment pipelines?
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Monthly 'Shameless Self Promotion' thread - 2023/01
A open-source set of Universal Helm Charts with tons of best-practices baked into it such as autoscaling, PDBs, labeling, and an standardized set of "universal" templates that allows you to pivot between templates easily (meaning, you can easily make a deployment into a Statefulset or a Cronjob). Yes, I need to add more documentation, I know. I'm busy :P
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Creating Kubernetes Templates
Universal Kubernetes Helm Charts
kind
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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:
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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.
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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.
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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.
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Mykube - simple cli for single node K8S creatiom
Features compared to https://kind.sigs.k8s.io/
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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.
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Choosing the Next Step: Docker Swarm or Kubernetes After Mastering Docker?
Check out KinD
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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.
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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.
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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
What are some alternatives?
Helm-Chart-Boilerplates - Example implementations of the universal helm charts
minikube - Run Kubernetes locally
charts - TrueNAS SCALE Apps Catalogs & Charts
k3d - Little helper to run CNCF's k3s in Docker
Packer - Packer is a tool for creating identical machine images for multiple platforms from a single source configuration.
lima - Linux virtual machines, with a focus on running containers
eksctl - The official CLI for Amazon EKS
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.
helm-promotion-sample-app - Sample application that is promoted from QA to Staging to Production
colima - Container runtimes on macOS (and Linux) with minimal setup
Chalice-PynamoDB-Docker-Starter-Kit - A starter kit with some boilerplate code for getting started making low-cost serverless applications in Python on AWS with a great local development setup via Docker Compose
nerdctl - contaiNERD CTL - Docker-compatible CLI for containerd, with support for Compose, Rootless, eStargz, OCIcrypt, IPFS, ...