Docker vs Kubernetes

Docker creates a single object, containing an application with its dependencies, that can be moved between any docker-enabled machines, guaranteeing the same environment for application execution.

Docker tracks changes in systems. It allows for commits and rollbacks and for quick deployment due to having to deploy only the updated code.

Docker essentially allows creating boilerplate systems (a LAMP stack, for example) that can be used as a starting point on multiple projects. And you can find multiple such containers already created by people in their public registry.

Allows automatically assembling a container from its source code.

Docker allows easily pushing and pulling containers to and from their public index.docker.io registry. Additionally, dotCloud maintains a list of official repositories of the more popular containers.

You can set up Docker within an already virtualized environment such as a virtual machine. This allows you to run Docker on Mac and Windows, among other use-cases.

Docker can be used with OpenVZ, systemd-nspawn, libvirt-lxc, libvirt-sandbox, qemu/kvm, BSD Jails, Solaris Zones, and chroot.

Kubernetes is free and open source.

Kubernetes was built on top of several years of experience from Google working on containers in production. It's a little opinionated on how containers should work and behave, but if used correctly it can help you achieve fault-tolerant systems.

Almost everything in Kubernetes is designed to handle if parts of it fail or if your service crashed for whatever reason. So it's particularly adapted if you've a cluster (even a very small one).

Kubernetes works very well with modern environments (such as CoreOS or Red Hat Atomc) which offer lightweight computing nodes that you don't have to manage, since they are managed for you.

Kubernetes is currently supported by Google Compute Engine, Rackspace, Microsoft Azure, and vSphere. Work is being done to support Kubernetes on OpenShift and CloudFoundry.

Kubernetes uses labels which are key-value pairs that are attached to objects, usually pods. They are used to specify the characteristics of an object like the version, tier, etc. Labels are used to identify objects or groups of objects according to different characteristics that they may have, for example they can be used to identify all the pods that are included in the backend tier.

Through labels it's easier to do grouping tasks for pods or containers, like moving pods to different groups or assigning them to load-balanced groups.

Kubernetes great for beginners who are just starting to work on clustering. It's probably the quickest and easiest way to start experimenting and learning cluster oriented development.