chruby VS kind

I think Capistrano is a good example. Their homepage snippet shows you what a DSL is.

I think it's something like https://capistranorb.com/

That should give you lots of stuff to research but I'll leave you with a final point: Every project is going to be different. Use the right tool for the right job; for a small application you definitely don't need Kubernetes, you might be fine without any pipeline at all. For example, Ruby on Rails projects can use a tool called capistrano to script deploys and you can run that from your local machine any time you need to deploy when your project is still small. As the project grows, you can start thinking about creating a pipeline that simply leverages capistrano from say GH actions or something. The point is, don't go crazy with pipelines - do the minimum amount to make the process smooth and focus the rest of your time and energy on the application itself as that's what the users will actually see and use. Users don't care if you use kubernetes or not.

I personally consider Jenkins a Task Runner that has a massive collection of CI plugins. Anyone can do deployments/delivery from a task runner, but any deployments I had to do in Jenkins ended up needing custom code written to do the actual work. This isn't unique to Jenkins; before the days of kubernetes, we had tools like capistrano or Config Management tools like Chef and Puppet that were capable of doing code deployments.

Two deployment techs I use for non-containerized apps work in roughly the same way. Capistrano And Deployer.

I have a Ruby background where I used to have Capistrano https://capistranorb.com/ for this reason. I was setting up the IP Address, path, SSH credentials, github repository and by executing a command I was able to deploy to a remote server.

The deployment process generally includes making the new version available, directing traffic from the old to the new version, and stopping the old versions. Capistrano has been doing this since 2006. However, what makes Kubernetes deployments better is the minimum number of pods required, and its rollout strategy minimizes or eliminates downtime. For example, a rolling update strategy can ensure new pods gradually replace old pods with configs like maxSurge and maxUnavailable. Because this is done in a declarative way, as a user or operator, you only need to ask Kubernetes to apply a given deployment and Kubernetes does the rest. Next up is the Kubernetes config map.

Has worked well for us on various projects for the past 18 months - prior to that we were using Capistrano.

# Load DSL and set up stages require "capistrano/setup" # Include default deployment tasks require "capistrano/deploy" require 'capistrano/rails' require 'capistrano/bundler' require 'capistrano/rbenv' require 'capistrano/puma' install_plugin Capistrano::Puma::Daemon install_plugin Capistrano::Puma # Load the SCM plugin appropriate to your project: # # require "capistrano/scm/hg" # install_plugin Capistrano::SCM::Hg # or # require "capistrano/scm/svn" # install_plugin Capistrano::SCM::Svn # or require "capistrano/scm/git" install_plugin Capistrano::SCM::Git # Include tasks from other gems included in your Gemfile # # For documentation on these, see for example: # # https://github.com/capistrano/rvm # https://github.com/capistrano/rbenv # https://github.com/capistrano/chruby # https://github.com/capistrano/bundler # https://github.com/capistrano/rails # https://github.com/capistrano/passenger # # Load custom tasks from `lib/capistrano/tasks` if you have any defined Dir.glob("lib/capistrano/tasks/*.rake").each { |r| import r } My installed gems gem "capistrano", require: false gem "capistrano-rails", require: false gem 'capistrano3-puma', require: false gem 'capistrano-rbenv'

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