When comparing Docker vs Kubernetes, the Slant community recommends Docker for most people. In the question“What are the best Linux container management systems?” Docker is ranked 1st while Kubernetes is ranked 2nd.
Ranked in these QuestionsQuestion Ranking
Pro Low overhead
Pro Allows for portable application deployment
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.
Pro Git-like capabilities
Docker tracks changes in systems. It allows for commits and rollbacks and for quick deployment due to having to deploy only the updated code.
Pro Allows re-using components
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.
Pro Automatic build
Allows automatically assembling a container from its source code.
Pro Provides easy sharing and installation of containers through a public registry
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.
Pro Works in virtualized environments
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.
Pro Supports a wide range of isolation tools
Docker can be used with OpenVZ, systemd-nspawn, libvirt-lxc, libvirt-sandbox, qemu/kvm, BSD Jails, Solaris Zones, and chroot.
Pro Tool ecosystem
Pro Supported on several PaaS
Kubernetes is currently supported by Google Compute Engine, Rackspace, Microsoft Azure, and vSphere. Work is being done to support Kubernetes on OpenShift and CloudFoundry.
Pro Works well with modern operating systems
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.
Pro Easy to do grouping tasks
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.
Pro Open Source
Kubernetes is free and open source.
Pro Built on several years of experience with containers
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.
Pro Fault tolerant
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).
Pro Great starting point for beginners
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.
Con Large image size
Con Security concerns
Con Kernel OS fragmentation
Con If used on an existing system, some re-organizing may be needed
Because of how opinionated Kubernetes is, it may be necessary to change some things if you decide to use Kubernetes as an orchestration tool in an existing application.
Con Sometimes Pods refuse to (re)start automatically
It happens that a Pod needs a manual kick before it runs properly, especially if you're near full utilisation of your machine resources. Sometimes it is just a long delay.
Con Cannot define containers through the Docker CLI
Kubernetes was not written for docker clustering alone. It uses a different API, configuration and different YAML definitions. So you can't use the Docker CLI or Docker Compose to define your containers. Everything has to be done from scratch.