chruby VS kubernetes

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'

In the field of software development, efficiency and agility are always sought after. In the era of cloud-native apps, traditional deployment techniques—which are frequently laborious and prone to errors—are starting to become obstacles. This is when Kubernetes and GitOps come in handy.

Are you looking for a hassle-free way to deploy Moodle™ Learning Management Systems (LMS) on Kubernetes? Look no further! Krestomatio presents the LMS Moodle Operator, an open-source Kubernetes Operator designed to simplify the deployment and management of Moodle instances on Kubernetes clusters. Let's dive into what makes this tool a great choice for Moodle administrators and developers alike.

Securing access to your Kubernetes clusters is crucial as inadequate security measures can lead to unauthorized access and potential data breaches. However, navigating the complexities of Kubernetes access security, especially when setting up strong authentication, authorization, and network policies, can be challenging.

Deploying AI models into production requires tools that can package applications and manage them at scale. Docker simplifies the deployment of AI applications by containerizing them, ensuring that the application runs smoothly in any environment. Kubernetes, an orchestration system for Docker containers, allows for the automated deployment, scaling, and management of containerized applications, essential for AI applications that need to scale across multiple servers or cloud environments.

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.