1623754440
Containers Demystified & Why Kubernetes Depreciated Docker
In this article, we will be covering all the details about containers i.e. how they actually work behind the scene and all the parts it consists of. We will also learn why Docker is so blazingly fast.
By the end of this article you will be able to create your own custom container. Excited already? Well you should definitely be.
We will see why K8S depreciated Docker and adopted CRI-O & we will also see how to set up a multi-node Kubernetes cluster using CRI-O
What are containers?
Containers are a solution to the problem of how to get the software to run reliably when moved from one computing environment to another. Container technology is almost as old as VMs, although the IT industry wasn’t employing containers until 2013–14 when Docker and Kubernetes, and other tech made waves were born that caused craziness in the industry. Containers have become a major trend in software development as an alternative or companion to Virtual Machine. Containerization helps developers to create and deploy applications faster and more securely.
Why do you need them?
Containers are a solution to the problem of how to get the software to run reliably when moved from one computing environment to another. This could be from a developer’s laptop to a test environment, from a staging environment into production, and perhaps from a physical machine in a data center to a virtual machine in a private or public cloud.
Problems arise when the supporting software environment is not identical, says Docker creator Solomon Hykes. “You’re going to test using Python 2.7, and then it’s going to run on Python 3 in production and something weird will happen. Or you’ll rely on the behavior of a certain version of an SSL library and another one will be installed. You’ll run your tests on Debian and production is on Red Hat and all sorts of weird things happen.”
And it’s not just different software that can cause problems, he added. “The network topology might be different, or the security policies and storage might be different but the software has to run on it.”
#kubernetes #docker #podman #containers #devops
What is GEEK
Buddha Community
1602964260
50+ Useful Kubernetes Tools for 2020 - Part 2
Introduction
Last year, we provided a list of Kubernetes tools that proved so popular we have decided to curate another list of some useful additions for working with the platform—among which are many tools that we personally use here at Caylent. Check out the original tools list here in case you missed it.
According to a recent survey done by Stackrox, the dominance Kubernetes enjoys in the market continues to be reinforced, with 86% of respondents using it for container orchestration.
And as you can see below, more and more companies are jumping into containerization for their apps. If you’re among them, here are some tools to aid you going forward as Kubernetes continues its rapid growth.
#blog #tools #amazon elastic kubernetes service #application security #aws kms #botkube #caylent #cli #container monitoring #container orchestration tools #container security #containers #continuous delivery #continuous deployment #continuous integration #contour #developers #development #developments #draft #eksctl #firewall #gcp #github #harbor #helm #helm charts #helm-2to3 #helm-aws-secret-plugin #helm-docs #helm-operator-get-started #helm-secrets #iam #json #k-rail #k3s #k3sup #k8s #keel.sh #keycloak #kiali #kiam #klum #knative #krew #ksniff #kube #kube-prod-runtime #kube-ps1 #kube-scan #kube-state-metrics #kube2iam #kubeapps #kubebuilder #kubeconfig #kubectl #kubectl-aws-secrets #kubefwd #kubernetes #kubernetes command line tool #kubernetes configuration #kubernetes deployment #kubernetes in development #kubernetes in production #kubernetes ingress #kubernetes interfaces #kubernetes monitoring #kubernetes networking #kubernetes observability #kubernetes plugins #kubernetes secrets #kubernetes security #kubernetes security best practices #kubernetes security vendors #kubernetes service discovery #kubernetic #kubesec #kubeterminal #kubeval #kudo #kuma #microsoft azure key vault #mozilla sops #octant #octarine #open source #palo alto kubernetes security #permission-manager #pgp #rafay #rakess #rancher #rook #secrets operations #serverless function #service mesh #shell-operator #snyk #snyk container #sonobuoy #strongdm #tcpdump #tenkai #testing #tigera #tilt #vert.x #wireshark #yaml
1623754440
Containers Demystified & Why Kubernetes Depreciated Docker
In this article, we will be covering all the details about containers i.e. how they actually work behind the scene and all the parts it consists of. We will also learn why Docker is so blazingly fast.
By the end of this article you will be able to create your own custom container. Excited already? Well you should definitely be.
We will see why K8S depreciated Docker and adopted CRI-O & we will also see how to set up a multi-node Kubernetes cluster using CRI-O
What are containers?
Containers are a solution to the problem of how to get the software to run reliably when moved from one computing environment to another. Container technology is almost as old as VMs, although the IT industry wasn’t employing containers until 2013–14 when Docker and Kubernetes, and other tech made waves were born that caused craziness in the industry. Containers have become a major trend in software development as an alternative or companion to Virtual Machine. Containerization helps developers to create and deploy applications faster and more securely.
Why do you need them?
Containers are a solution to the problem of how to get the software to run reliably when moved from one computing environment to another. This could be from a developer’s laptop to a test environment, from a staging environment into production, and perhaps from a physical machine in a data center to a virtual machine in a private or public cloud.
Problems arise when the supporting software environment is not identical, says Docker creator Solomon Hykes. “You’re going to test using Python 2.7, and then it’s going to run on Python 3 in production and something weird will happen. Or you’ll rely on the behavior of a certain version of an SSL library and another one will be installed. You’ll run your tests on Debian and production is on Red Hat and all sorts of weird things happen.”
And it’s not just different software that can cause problems, he added. “The network topology might be different, or the security policies and storage might be different but the software has to run on it.”
#kubernetes #docker #podman #containers #devops
1597384020
Kubernetes vs Docker Swarm
·Installation and Cluster configuration
Kubernetes:
Setting up a cluster manually is complex. The configurations differ between different operating systems. It requires a lot of pre-planning as far as the setup goes. Components like storage and networks require configurations. Third-party packages like kubectl etc are required.
Docker Swarm:
Installing Docker Swarm clusters is simple. It only requires a few commands to setup a cluster, and then to add further worker or manager nodes. The setup is also OS independent, and so developers don’t have to spend any time learning new commands based on the OS.
· Load balancing
Kubernetes:
It has to be setup manually but is not very complicated. An ingress can be used to load balancing. Pods are exposed as a service.
Docker Swarm:
Load balancing is done by default and ports are assigned automatically. All containers from a cluster remain in a common network.
#docker #container-orchestration #containers #kubernetes #docker-swarm
1602317778
Ever Wondered Why We Use Containers In DevOps?
At some point we’ve all said the words, “But it works on my machine.” It usually happens during testing or when you’re trying to get a new project set up. Sometimes it happens when you pull down changes from an updated branch.
Every machine has different underlying states depending on the operating system, other installed programs, and permissions. Getting a project to run locally could take hours or even days because of weird system issues.
The worst part is that this can also happen in production. If the server is configured differently than what you’re running locally, your changes might not work as you expect and cause problems for users. There’s a way around all of these common issues using containers.
What is a container
A container is a piece of software that packages code and its dependencies so that the application can run in any computing environment. They basically create a little unit that you can put on any operating system and reliably and consistently run the application. You don’t have to worry about any of those underlying system issues creeping in later.
Although containers were already used in Linux for years, they became more popular in recent years. Most of the time when people are talking about containers, they’re referring to Docker containers. These containers are built from images that include all of the dependencies needed to run an application.
When you think of containers, virtual machines might also come to mind. They are very similar, but the big difference is that containers virtualize the operating system instead of the hardware. That’s what makes them so easy to run on all of the operating systems consistently.
What containers have to do with DevOps
Since we know how odd happenings occur when you move code from one computing environment to another, this is also a common issue with moving code to the different environments in our DevOps process. You don’t want to have to deal with system differences between staging and production. That would require more work than it should.
Once you have an artifact built, you should be able to use it in any environment from local to production. That’s the reason we use containers in DevOps. It’s also invaluable when you’re working with microservices. Docker containers used with something like Kubernetes will make it easier for you to handle larger systems with more moving pieces.
#devops #containers #containers-devops #devops-containers #devops-tools #devops-docker #docker #docker-image
1597368540
Docker Tutorial for Beginners 8 - Build and Run C++ Applications in a Docker Container
Docker is an open platform that allows use package, develop, run, and ship software applications in different environments using containers.
In this course We will learn How to Write Dockerfiles, Working with the Docker Toolbox, How to Work with the Docker Machine, How to Use Docker Compose to fire up multiple containers, How to Work with Docker Kinematic, Push images to Docker Hub, Pull images from a Docker Registery, Push stacks of servers to Docker Hub.
How to install Docker on Mac.
#docker tutorial #c++ #docker container #docker #docker hub #devopstools