If you take a look at Docker's features, most of them are already provided by LXC.
So what does Docker add? Why would I use Docker over plain LXC?
If you take a look at Docker's features, most of them are already provided by LXC.
So what does Docker add? Why would I use Docker over plain LXC?
Going to keep this pithier, this is already asked and answered above .
I'd step back however and answer it slightly differently, the docker engine itself adds orchestration as one of its extras and this is the disruptive part. Once you start running an app as a combination of containers running 'somewhere' across multiple container engines it gets really exciting. Robustness, Horizontal Scaling, complete abstraction from the underlying hardware, i could go on and on...
Its not just Docker that gives you this, in fact the de facto Container Orchestration standard is Kubernetes which comes in a lot of flavours, a Docker one, but also OpenShift, SuSe, Azure, AWS...
Then beneath K8S there are alternative container engines; the interesting ones are Docker and CRIO - recently built, daemonless, intended as a container engine specifically for Kubernetes but immature. Its the competition between these that I think will be the real long term choice for a container engine.
Let's take a look at the list of Docker's technical features, and check which ones are provided by LXC and which ones aren't.
Features:
Provided with plain LXC.
Provided with plain LXC.
Provided with plain LXC.
This is provided by AUFS, a union filesystem that Docker depends on. You could set up AUFS yourself manually with LXC, but Docker uses it as a standard.
Docker provides this.
"Templating or manual configuration" is a reference to LXC, where you would need to learn about both of these things. Docker allows you to treat containers in the way that you're used to treating virtual machines, without learning about LXC configuration.
LXC already provides this.
I only just started learning about LXC and Docker, so I'd welcome any corrections or better answers.
Dockers use images which are build in layers. This adds a lot in terms of portability, sharing, versioning and other features. These images are very easy to port or transfer and since they are in layers, changes in subsequent versions are added in form of layers over previous layers. So, while porting many a times you don't need to port the base layers. Dockers have containers which run these images with execution environment contained, they add changes as new layers providing easy version control.
Apart from that Docker Hub is a good registry with thousands of public images, where you can find images which have OS and other softwares installed. So, you can get a pretty good head start for your application.
The above post & answers are rapidly becoming dated as the development of LXD continues to enhance LXC. Yes, I know Docker hasn't stood still either.
LXD now implements a repository for LXC container images which a user can push/pull from to contribute to or reuse.
LXD's REST api to LXC now enables both local & remote creation/deployment/management of LXC containers using a very simple command syntax.
Key features of LXD are:
There is NCLXD plugin now for OpenStack allowing OpenStack to utilize LXD to deploy/manage LXC containers as VMs in OpenStack instead of using KVM, vmware etc.
However, NCLXD also enables a hybrid cloud of a mix of traditional HW VMs and LXC VMs.
The OpenStack nclxd plugin a list of features supported include:
By the time Ubuntu 16.04 is released in Apr 2016 there will have been additional cool features such as block device support, live-migration support.
From the Docker FAQ:
Docker is not a replacement for lxc. "lxc" refers to capabilities of the linux kernel (specifically namespaces and control groups) which allow sandboxing processes from one another, and controlling their resource allocations.
On top of this low-level foundation of kernel features, Docker offers a high-level tool with several powerful functionalities:
Portable deployment across machines. Docker defines a format for bundling an application and all its dependencies into a single object which can be transferred to any docker-enabled machine, and executed there with the guarantee that the execution environment exposed to the application will be the same. Lxc implements process sandboxing, which is an important pre-requisite for portable deployment, but that alone is not enough for portable deployment. If you sent me a copy of your application installed in a custom lxc configuration, it would almost certainly not run on my machine the way it does on yours, because it is tied to your machine's specific configuration: networking, storage, logging, distro, etc. Docker defines an abstraction for these machine-specific settings, so that the exact same docker container can run - unchanged - on many different machines, with many different configurations.
Application-centric. Docker is optimized for the deployment of applications, as opposed to machines. This is reflected in its API, user interface, design philosophy and documentation. By contrast, the lxc helper scripts focus on containers as lightweight machines - basically servers that boot faster and need less ram. We think there's more to containers than just that.
Automatic build. Docker includes a tool for developers to automatically assemble a container from their source code, with full control over application dependencies, build tools, packaging etc. They are free to use make, maven, chef, puppet, salt, debian packages, rpms, source tarballs, or any combination of the above, regardless of the configuration of the machines.
Versioning. Docker includes git-like capabilities for tracking successive versions of a container, inspecting the diff between versions, committing new versions, rolling back etc. The history also includes how a container was assembled and by whom, so you get full traceability from the production server all the way back to the upstream developer. Docker also implements incremental uploads and downloads, similar to "git pull", so new versions of a container can be transferred by only sending diffs.
Component re-use. Any container can be used as an "base image" to create more specialized components. This can be done manually or as part of an automated build. For example you can prepare the ideal python environment, and use it as a base for 10 different applications. Your ideal postgresql setup can be re-used for all your future projects. And so on.
Sharing. Docker has access to a public registry (https://registry.hub.docker.com/) where thousands of people have uploaded useful containers: anything from redis, couchdb, postgres to irc bouncers to rails app servers to hadoop to base images for various distros. The registry also includes an official "standard library" of useful containers maintained by the docker team. The registry itself is open-source, so anyone can deploy their own registry to store and transfer private containers, for internal server deployments for example.
Tool ecosystem. Docker defines an API for automating and customizing the creation and deployment of containers. There are a huge number of tools integrating with docker to extend its capabilities. PaaS-like deployment (Dokku, Deis, Flynn), multi-node orchestration (maestro, salt, mesos, openstack nova), management dashboards (docker-ui, openstack horizon, shipyard), configuration management (chef, puppet), continuous integration (jenkins, strider, travis), etc. Docker is rapidly establishing itself as the standard for container-based tooling.
I hope this helps!