Docker: the Linux container engine

Docker is an open source project to pack, ship and run any application as a lightweight container

Docker containers are both hardware-agnostic and platform-agnostic. This means they can run anywhere, from your laptop to the largest EC2 compute instance and everything in between - and they don't require you to use a particular language, framework or packaging system. That makes them great building blocks for deploying and scaling web apps, databases, and backend services without depending on a particular stack or provider.

Docker began as an open-source implementation of the deployment engine which powers dotCloud, a popular Platform-as-a-Service. It benefits directly from the experience accumulated over several years of large-scale operation and support of hundreds of thousands of applications and databases.

Security Disclosure

Security is very important to us. If you have any issue regarding security, please disclose the information responsibly by sending an email to security@docker.com and not by creating a github issue.

Better than VMs

A common method for distributing applications and sandboxing their execution is to use virtual machines, or VMs. Typical VM formats are VMWare's vmdk, Oracle Virtualbox's vdi, and Amazon EC2's ami. In theory these formats should allow every developer to automatically package their application into a "machine" for easy distribution and deployment. In practice, that almost never happens, for a few reasons:

• Size: VMs are very large which makes them impractical to store and transfer.
• Performance: running VMs consumes significant CPU and memory, which makes them impractical in many scenarios, for example local development of multi-tier applications, and large-scale deployment of cpu and memory-intensive applications on large numbers of machines.
• Portability: competing VM environments don't play well with each other. Although conversion tools do exist, they are limited and add even more overhead.
• Hardware-centric: VMs were designed with machine operators in mind, not software developers. As a result, they offer very limited tooling for what developers need most: building, testing and running their software. For example, VMs offer no facilities for application versioning, monitoring, configuration, logging or service discovery.

By contrast, Docker relies on a different sandboxing method known as containerization. Unlike traditional virtualization, containerization takes place at the kernel level. Most modern operating system kernels now support the primitives necessary for containerization, including Linux with openvz, vserver and more recently lxc, Solaris with zones, and FreeBSD with Jails.

Docker builds on top of these low-level primitives to offer developers a portable format and runtime environment that solves all four problems. Docker containers are small (and their transfer can be optimized with layers), they have basically zero memory and cpu overhead, they are completely portable, and are designed from the ground up with an application-centric design.

Perhaps best of all, because Docker operates at the OS level, it can still be run inside a VM!

Plays well with others

Docker does not require you to buy into a particular programming language, framework, packaging system, or configuration language.

Is your application a Unix process? Does it use files, tcp connections, environment variables, standard Unix streams and command-line arguments as inputs and outputs? Then Docker can run it.

Can your application's build be expressed as a sequence of such commands? Then Docker can build it.

Escape dependency hell

A common problem for developers is the difficulty of managing all their application's dependencies in a simple and automated way.

This is usually difficult for several reasons:

• Cross-platform dependencies. Modern applications often depend on a combination of system libraries and binaries, language-specific packages, framework-specific modules, internal components developed for another project, etc. These dependencies live in different "worlds" and require different tools - these tools typically don't work well with each other, requiring awkward custom integrations.

• Conflicting dependencies. Different applications may depend on different versions of the same dependency. Packaging tools handle these situations with various degrees of ease - but they all handle them in different and incompatible ways, which again forces the developer to do extra work.

• Custom dependencies. A developer may need to prepare a custom version of their application's dependency. Some packaging systems can handle custom versions of a dependency, others can't - and all of them handle it differently.

Docker solves the problem of dependency hell by giving the developer a simple way to express all their application's dependencies in one place, while streamlining the process of assembling them. If this makes you think of XKCD 927, don't worry. Docker doesn't replace your favorite packaging systems. It simply orchestrates their use in a simple and repeatable way. How does it do that? With layers.

Docker defines a build as running a sequence of Unix commands, one after the other, in the same container. Build commands modify the contents of the container (usually by installing new files on the filesystem), the next command modifies it some more, etc. Since each build command inherits the result of the previous commands, the order in which the commands are executed expresses dependencies.

Here's a typical Docker build process:

FROM ubuntu:12.04
RUN apt-get update && apt-get install -y python python-pip curl
RUN curl -sSL https://github.com/shykes/helloflask/archive/master.tar.gz | tar -xzv
RUN cd helloflask-master && pip install -r requirements.txt

Note that Docker doesn't care how dependencies are built - as long as they can be built by running a Unix command in a container.

Getting started

Docker can be installed on your local machine as well as servers - both bare metal and virtualized. It is available as a binary on most modern Linux systems, or as a VM on Windows, Mac and other systems.

We also offer an interactive tutorial for quickly learning the basics of using Docker.

For up-to-date install instructions, see the Docs.

Usage examples

Docker can be used to run short-lived commands, long-running daemons (app servers, databases etc.), interactive shell sessions, etc.

You can find a list of real-world examples in the documentation.

Under the hood

Under the hood, Docker is built on the following components:

• The cgroup and namespacing capabilities of the Linux kernel;
• The Go programming language.

Contributing to Docker

Want to hack on Docker? Awesome! We have instructions to help you get started. If you'd like to contribute to the documentation, please take a look at this README.md.

These instructions are probably not perfect, please let us know if anything feels wrong or incomplete. Better yet, submit a PR and improve them yourself.

Want to run Docker from a master build? You can download master builds at master.dockerproject.com. They are updated with each commit merged into the master branch.

Legal

Brought to you courtesy of our legal counsel. For more context, please see the "NOTICE" document in this repo.

Use and transfer of Docker may be subject to certain restrictions by the United States and other governments.
It is your responsibility to ensure that your use and/or transfer does not violate applicable laws.

For more information, please see http://www.bis.doc.gov

Licensing

Docker is licensed under the Apache License, Version 2.0. See LICENSE for the full license text.

Other Docker Related Projects

There are a number of projects under development that are based on Docker's core technology. These projects expand the tooling built around the Docker platform to broaden its application and utility.

If you know of another project underway that should be listed here, please help us keep this list up-to-date by submitting a PR.

• Docker Registry: Registry server for Docker (hosting/delivering of repositories and images)
• Docker Machine: Machine management for a container-centric world
• Docker Swarm: A Docker-native clustering system
• Docker Compose, aka Fig: Multi-container application management