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clean up unused nats code

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Signed-off-by: Akihiro Suda <suda.akihiro@lab.ntt.co.jp>
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Akihiro Suda 2017-02-20 05:26:36 +00:00
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Docker: the container engine [![Release](https://img.shields.io/github/release/docker/docker.svg)](https://github.com/docker/docker/releases/latest)
============================
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
cloud 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
powered [dotCloud](http://web.archive.org/web/20130530031104/https://www.dotcloud.com/),
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.
![Docker logo](docs/static_files/docker-logo-compressed.png "Docker")
## 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](https://openvz.org),
[vserver](http://linux-vserver.org) and more recently
[lxc](https://linuxcontainers.org/), Solaris with
[zones](https://docs.oracle.com/cd/E26502_01/html/E29024/preface-1.html#scrolltoc),
and FreeBSD with
[Jails](https://www.freebsd.org/doc/handbook/jails.html).
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](https://xkcd.com/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:
```bash
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 either on your computer for building applications or
on servers for running them. To get started, [check out the installation
instructions in the
documentation](https://docs.docker.com/engine/installation/).
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](https://docs.docker.com/engine/examples/) in the
documentation.
Under the hood
--------------
Under the hood, Docker is built on the following components:
* The
[cgroups](https://www.kernel.org/doc/Documentation/cgroup-v1/cgroups.txt)
and
[namespaces](http://man7.org/linux/man-pages/man7/namespaces.7.html)
capabilities of the Linux kernel
* The [Go](https://golang.org) programming language
* The [Docker Image Specification](https://github.com/docker/docker/blob/master/image/spec/v1.md)
* The [Libcontainer Specification](https://github.com/opencontainers/runc/blob/master/libcontainer/SPEC.md)
Contributing to Docker [![GoDoc](https://godoc.org/github.com/docker/docker?status.svg)](https://godoc.org/github.com/docker/docker)
======================
| **Master** (Linux) | **Experimental** (Linux) | **Windows** | **FreeBSD** |
|------------------|----------------------|---------|---------|
| [![Jenkins Build Status](https://jenkins.dockerproject.org/view/Docker/job/Docker%20Master/badge/icon)](https://jenkins.dockerproject.org/view/Docker/job/Docker%20Master/) | [![Jenkins Build Status](https://jenkins.dockerproject.org/view/Docker/job/Docker%20Master%20%28experimental%29/badge/icon)](https://jenkins.dockerproject.org/view/Docker/job/Docker%20Master%20%28experimental%29/) | [![Build Status](http://jenkins.dockerproject.org/job/Docker%20Master%20(windows)/badge/icon)](http://jenkins.dockerproject.org/job/Docker%20Master%20(windows)/) | [![Build Status](http://jenkins.dockerproject.org/job/Docker%20Master%20(freebsd)/badge/icon)](http://jenkins.dockerproject.org/job/Docker%20Master%20(freebsd)/) |
Want to hack on Docker? Awesome! We have [instructions to help you get
started contributing code or documentation](https://docs.docker.com/opensource/project/who-written-for/).
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.
Getting the development builds
==============================
Want to run Docker from a master build? You can download
master builds at [master.dockerproject.org](https://master.dockerproject.org).
They are updated with each commit merged into the master branch.
Don't know how to use that super cool new feature in the master build? Check
out the master docs at
[docs.master.dockerproject.org](http://docs.master.dockerproject.org).
How the project is run
======================
Docker is a very, very active project. If you want to learn more about how it is run,
or want to get more involved, the best place to start is [the project directory](https://github.com/docker/docker/tree/master/project).
We are always open to suggestions on process improvements, and are always looking for more maintainers.
### Talking to other Docker users and contributors
<table class="tg">
<col width="45%">
<col width="65%">
<tr>
<td>Internet&nbsp;Relay&nbsp;Chat&nbsp;(IRC)</td>
<td>
<p>
IRC is a direct line to our most knowledgeable Docker users; we have
both the <code>#docker</code> and <code>#docker-dev</code> group on
<strong>irc.freenode.net</strong>.
IRC is a rich chat protocol but it can overwhelm new users. You can search
<a href="https://botbot.me/freenode/docker/#" target="_blank">our chat archives</a>.
</p>
Read our <a href="https://docs.docker.com/opensource/get-help/#/irc-quickstart" target="_blank">IRC quickstart guide</a> for an easy way to get started.
</td>
</tr>
<tr>
<td>Docker Community Forums</td>
<td>
The <a href="https://forums.docker.com/c/open-source-projects/de" target="_blank">Docker Engine</a>
group is for users of the Docker Engine project.
</td>
</tr>
<tr>
<td>Google Groups</td>
<td>
The <a href="https://groups.google.com/forum/#!forum/docker-dev"
target="_blank">docker-dev</a> group is for contributors and other people
contributing to the Docker project. You can join this group without a
Google account by sending an email to <a
href="mailto:docker-dev+subscribe@googlegroups.com">docker-dev+subscribe@googlegroups.com</a>.
You'll receive a join-request message; simply reply to the message to
confirm your subscription.
</td>
</tr>
<tr>
<td>Twitter</td>
<td>
You can follow <a href="https://twitter.com/docker/" target="_blank">Docker's Twitter feed</a>
to get updates on our products. You can also tweet us questions or just
share blogs or stories.
</td>
</tr>
<tr>
<td>Stack Overflow</td>
<td>
Stack Overflow has over 7000 Docker questions listed. We regularly
monitor <a href="https://stackoverflow.com/search?tab=newest&q=docker" target="_blank">Docker questions</a>
and so do many other knowledgeable Docker users.
</td>
</tr>
</table>
### Legal
*Brought to you courtesy of our legal counsel. For more context,
please see the [NOTICE](https://github.com/docker/docker/blob/master/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 https://www.bis.doc.gov
Licensing
=========
Docker is licensed under the Apache License, Version 2.0. See
[LICENSE](https://github.com/docker/docker/blob/master/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.
* [Docker Registry](https://github.com/docker/distribution): Registry
server for Docker (hosting/delivery of repositories and images)
* [Docker Machine](https://github.com/docker/machine): Machine management
for a container-centric world
* [Docker Swarm](https://github.com/docker/swarm): A Docker-native clustering
system
* [Docker Compose](https://github.com/docker/compose) (formerly Fig):
Define and run multi-container apps
* [Kitematic](https://github.com/docker/kitematic): The easiest way to use
Docker on Mac and Windows
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.
Awesome-Docker
==============
You can find more projects, tools and articles related to Docker on the [awesome-docker list](https://github.com/veggiemonk/awesome-docker). Add your project there.

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pkg/ is a collection of utility packages used by the Docker project without being specific to its internals.
Utility packages are kept separate from the docker core codebase to keep it as small and concise as possible.
If some utilities grow larger and their APIs stabilize, they may be moved to their own repository under the
Docker organization, to facilitate re-use by other projects. However that is not the priority.
The directory `pkg` is named after the same directory in the camlistore project. Since Brad is a core
Go maintainer, we thought it made sense to copy his methods for organizing Go code :) Thanks Brad!
Because utility packages are small and neatly separated from the rest of the codebase, they are a good
place to start for aspiring maintainers and contributors. Get in touch if you want to help maintain them!

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This code provides helper functions for dealing with archive files.

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# go-metrics [![GoDoc](https://godoc.org/github.com/docker/go-metrics?status.svg)](https://godoc.org/github.com/docker/go-metrics) ![Badge Badge](http://doyouevenbadge.com/github.com/docker/go-metrics)
This package is small wrapper around the prometheus go client to help enforce convention and best practices for metrics collection in Docker projects.
## Best Practices
This packages is meant to be used for collecting metrics in Docker projects.
It is not meant to be used as a replacement for the prometheus client but to help enforce consistent naming across metrics collected.
If you have not already read the prometheus best practices around naming and labels you can read the page [here](https://prometheus.io/docs/practices/naming/).
The following are a few Docker specific rules that will help you name and work with metrics in your project.
1. Namespace and Subsystem
This package provides you with a namespace type that allows you to specify the same namespace and subsystem for your metrics.
```go
ns := metrics.NewNamespace("engine", "daemon", metrics.Labels{
"version": dockerversion.Version,
"commit": dockerversion.GitCommit,
})
```
In the example above we are creating metrics for the Docker engine's daemon package.
`engine` would be the namespace in this example where `daemon` is the subsystem or package where we are collecting the metrics.
A namespace also allows you to attach constant labels to the metrics such as the git commit and version that it is collecting.
2. Declaring your Metrics
Try to keep all your metric declarations in one file.
This makes it easy for others to see what constant labels are defined on the namespace and what labels are defined on the metrics when they are created.
3. Use labels instead of multiple metrics
Labels allow you to define one metric such as the time it takes to perform a certain action on an object.
If we wanted to collect timings on various container actions such as create, start, and delete then we can define one metric called `container_actions` and use labels to specify the type of action.
```go
containerActions = ns.NewLabeledTimer("container_actions", "The number of milliseconds it takes to process each container action", "action")
```
The last parameter is the label name or key.
When adding a data point to the metric you will use the `WithValues` function to specify the `action` that you are collecting for.
```go
containerActions.WithValues("create").UpdateSince(start)
```
4. Always use a unit
The metric name should describe what you are measuring but you also need to provide the unit that it is being measured with.
For a timer, the standard unit is seconds and a counter's standard unit is a total.
For gauges you must provide the unit.
This package provides a standard set of units for use within the Docker projects.
```go
Nanoseconds Unit = "nanoseconds"
Seconds Unit = "seconds"
Bytes Unit = "bytes"
Total Unit = "total"
```
If you need to use a unit but it is not defined in the package please open a PR to add it but first try to see if one of the already created units will work for your metric, i.e. seconds or nanoseconds vs adding milliseconds.
## Docs
Package documentation can be found [here](https://godoc.org/github.com/docker/go-metrics).
## Additional Metrics
Additional metrics are also defined here that are not avaliable in the prometheus client.
If you need a custom metrics and it is generic enough to be used by multiple projects, define it here.
## Copyright and license
Copyright © 2016 Docker, Inc. All rights reserved, except as follows. Code is released under the Apache 2.0 license. The README.md file, and files in the "docs" folder are licensed under the Creative Commons Attribution 4.0 International License under the terms and conditions set forth in the file "LICENSE.docs". You may obtain a duplicate copy of the same license, titled CC-BY-SA-4.0, at http://creativecommons.org/licenses/by/4.0/.

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[![GoDoc](https://godoc.org/github.com/docker/go-units?status.svg)](https://godoc.org/github.com/docker/go-units)
# Introduction
go-units is a library to transform human friendly measurements into machine friendly values.
## Usage
See the [docs in godoc](https://godoc.org/github.com/docker/go-units) for examples and documentation.
## Copyright and license
Copyright © 2015 Docker, Inc.
go-units is licensed under the Apache License, Version 2.0.
See [LICENSE](LICENSE) for the full text of the license.