werf VS kind

I am looking as well for this kind of tool. I just took a look today by exploring the CNCF landscape this tool : https://werf.io/ , I haven't used it, but it seems to take care of painful stuff like automatic versioning for example. (If someone here tried it, I will be happy to listen to your feedbacks)

Werf - um ok

HybridK8s Droid - Intelligence foor your favourite Delivery Platform Devtron - Software Delivery Workflow for Kubernetes Skaffold - Easy and Repeatable Kubernetes Development Apollo - Apollo - The logz.io continuous deployment solution over kubernetes Helm Cabin - Web UI that visualizes Helm releases in a Kubernetes cluster flagger - Progressive delivery Kubernetes operator (Canary, A/B Testing and Blue/Green deployments) Kubeform - Kubernetes CRDs for Terraform providers https://kubeform.com Spinnaker - Spinnaker is an open source, multi-cloud continuous delivery platform for releasing software changes with high velocity and confidence. http://www.spinnaker.io/ werf - GitOps tool to deliver apps to Kubernetes and integrate this process with GitLab and other CI tools Flux - GitOps Kubernetes operator Argo CD - Declarative continuous deployment for Kubernetes Tekton - A cloud native continuous integration and delivery (CI/CD) solution Jenkins X - Jenkins X provides automated CI+CD for Kubernetes with Preview Environments on Pull Requests using Tekton, Knative, Lighthouse, Skaffold and Helm KubeVela - KubeVela works as an application delivery control plane that is fully decoupled from runtime infrastructure ksonnet - A CLI-supported framework that streamlines writing and deployment of Kubernetes configurations to multiple clusters CircleCI - A cloud-based tool that helps build continuous integration and continuous delivery pipelines to Kubernetes.

Check out https://werf.io/ tool. It features giterminism which is somewhat similar to gitops, but it does not require pull model. Giterminism aims to improve reproducibility of your build and deploy configuration. werf also features content-based-tagging out of the box, which allows creating immutable images, stored in the container-registry, shared between multiple runners (werf uses distributed locking to prevent overriding image which is already published). Giterminism and content-based-tagging enables easy rollbacks to any git-commit in the history of your project. By design werf could be embedded into any ci/cd system.

Rename of dapp to werf was in Jan'19 to be precise (https://github.com/werf/werf/pull/1213).

Werf

You can try werf, it has Helm under the hood and there are github actions available for it: https://github.com/werf/actions

As you know, there's plenty of tools that can be used to build your Docker images, besides the docker build itself. werf is an Open Source project with a long history (started in 2016 as a simple wrapper around Docker CLI). Still being a CLI tool, today it is focused not just on the building but also delivering these images to Kubernetes — and this is what makes it really different.

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:

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.

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.

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.

Features compared to https://kind.sigs.k8s.io/

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.

Check out KinD

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.

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.

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