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First draft of new README. Feedback and contributions welcome!
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README.md
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Docker: the Linux container runtime
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===================================
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Docker: the Linux container engine
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==================================
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Docker complements LXC with a high-level API which operates at the process level. It runs unix processes with strong guarantees of isolation and repeatability across servers.
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Docker is an open-source engine which automates the deployment of applications as highly portable, self-sufficient containers.
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Docker is a great building block for automating distributed systems: large-scale web deployments, database clusters, continuous deployment systems, private PaaS, service-oriented architectures, etc.
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Docker containers are both *hardware-agnostic* and *platform-agnostic*. This means that they can run anywhere, from your
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laptop to the largest EC2 compute instance and everything in between - and they don't require that you use a particular
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language, framework or packaging system. That makes them great building blocks for deploying and scaling web apps, databases
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and backend services without depending on a particular stack or provider.
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![Docker L](docs/sources/static_files/lego_docker.jpg "Docker")
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Docker is an open-source implementation of the deployment engine which powers [dotCloud](http://dotcloud.com), a popular Platform-as-a-Service.
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It benefits directly from the experience accumulated over several years of large-scale operation and support of hundreds of thousands
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of applications and databases.
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* *Heterogeneous payloads*: any combination of binaries, libraries, configuration files, scripts, virtualenvs, jars, gems, tarballs, you name it. No more juggling between domain-specific tools. Docker can deploy and run them all.
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## Better than VMs
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* *Any server*: docker can run on any x64 machine with a modern linux kernel - whether it's a laptop, a bare metal server or a VM. This makes it perfect for multi-cloud deployments.
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A common method for distributing applications and sandbox their execution is to use virtual machines, or VMs. Typical VM formats
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are VMWare's vmdk, Oracle Virtualbox's vdi, and Amazon EC2's ami. In theory these formats should allow every developer to
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automatically package their application into a "machine" for easy distribution and deployment. In practice, that almost never
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happens, for a few reasons:
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* *Isolation*: docker isolates processes from each other and from the underlying host, using lightweight containers.
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* *Size*: VMs are very large which makes them impractical to store and transfer.
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* *Performance*: running VMs consumes significant CPU and memory, which makes them impractical in many scenarios, for example local development of multi-tier applications, and
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large-scale deployment of cpu and memory-intensive applications on large numbers of machines.
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* *Portability*: competing VM environments don't play well with each other. Although conversion tools do exist, they are limited and add even more overhead.
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* *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:
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building, testing and running their software. For example, VMs offer no facilities for application versioning, monitoring, configuration, logging or service discovery.
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* *Repeatability*: because containers are isolated in their own filesystem, they behave the same regardless of where, when, and alongside what they run.
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By contrast, Docker relies on a different sandboxing method known as *containerization*. Unlike traditional virtualization,
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containerization takes place at the kernel level. Most modern operating system kernels now support the primitives necessary
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for containerization, including Linux with [openvz](http://openvz.org), [vserver](http://linux-vserver.org) and more recently [lxc](http://lxc.sourceforge.net),
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Solaris with [zones](http://docs.oracle.com/cd/E26502_01/html/E29024/preface-1.html#scrolltoc) and FreeBSD with [Jails](http://www.freebsd.org/doc/handbook/jails.html).
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Docker builds on top of these low-level primitives to offer developers a portable format and runtime environment that solves
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all 4 problems. Docker containers are small (and their transfer can be optimized with layers), they have basically zero memory and cpu overhead,
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the are completely portable and are designed from the ground up with an application-centric design.
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The best part: because docker operates at the OS level, it can still be run inside a VM!
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## Plays well with others
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Docker does not require that you buy into a particular programming language, framework, packaging system or configuration language.
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Is your application a unix process? Does it use files, tcp connections, environment variables, standard unix streams and command-line
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arguments as inputs and outputs? Then docker can run it.
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Can your application's build be expressed a sequence of such commands? Then docker can build it.
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Notable features
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-----------------
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## Escape dependency hell
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* Filesystem isolation: each process container runs in a completely separate root filesystem.
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A common problem for developers is the difficulty of managing all their application's dependencies in a simple and automated way.
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* Resource isolation: system resources like cpu and memory can be allocated differently to each process container, using cgroups.
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This is usually difficult for several reasons:
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* Network isolation: each process container runs in its own network namespace, with a virtual interface and IP address of its own.
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* *Cross-platform dependencies*. Modern applications often depend on a combination of system libraries and binaries, language-specific packages, framework-specific modules,
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internal components developed for another project, etc. These dependencies live in different "worlds" and require different tools - these tools typically don't work
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well with each other, requiring awkward custom integrations.
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* Copy-on-write: root filesystems are created using copy-on-write, which makes deployment extremely fast, memory-cheap and disk-cheap.
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* Conflicting dependencies. Different applications may depend on different versions of the same dependency. Packaging tools handle these situations with various degrees of ease -
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but they all handle them in different and incompatible ways, which again forces the developer to do extra work.
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* Custom dependencies. A developer may need to prepare a custom version of his application's dependency. Some packaging systems can handle custom versions of a dependency,
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others can't - and all of them handle it differently.
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* Logging: the standard streams (stdout/stderr/stdin) of each process container are collected and logged for real-time or batch retrieval.
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* Change management: changes to a container's filesystem can be committed into a new image and re-used to create more containers. No templating or manual configuration required.
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Docker solves dependency hell by giving the developer a simple way to express *all* his application's dependencies in one place,
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and streamline the process of assembling them. If this makes you think of [XKCD 927](http://xkcd.com/927/), don't worry. Docker doesn't
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*replace* your favorite packaging systems. It simply orchestrates their use in a simple and repeatable way. How does it do that? With layers.
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Docker defines a build as running a sequence unix commands, one after the other, in the same container. Build commands modify the contents of the container
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(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
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commands, the *order* in which the commands are executed expresses *dependencies*.
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Here's a typical docker build process:
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```bash
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from ubuntu:12.10
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run apt-get update
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run apt-get install python
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run apt-get install python-pip
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run pip install django
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run apt-get install curl
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run curl http://github.com/shykes/helloflask/helloflask/master.tar.gz | tar -zxv
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run cd master && pip install -r requirements.txt
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```
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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.
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* Interactive shell: docker can allocate a pseudo-tty and attach to the standard input of any container, for example to run a throwaway interactive shell.
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Install instructions
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==================
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