a793564b25
Moving all strings to the errors package wasn't a good idea after all.
Our custom implementation of Go errors predates everything that's nice
and good about working with errors in Go. Take as an example what we
have to do to get an error message:
```go
func GetErrorMessage(err error) string {
switch err.(type) {
case errcode.Error:
e, _ := err.(errcode.Error)
return e.Message
case errcode.ErrorCode:
ec, _ := err.(errcode.ErrorCode)
return ec.Message()
default:
return err.Error()
}
}
```
This goes against every good practice for Go development. The language already provides a simple, intuitive and standard way to get error messages, that is calling the `Error()` method from an error. Reinventing the error interface is a mistake.
Our custom implementation also makes very hard to reason about errors, another nice thing about Go. I found several (>10) error declarations that we don't use anywhere. This is a clear sign about how little we know about the errors we return. I also found several error usages where the number of arguments was different than the parameters declared in the error, another clear example of how difficult is to reason about errors.
Moreover, our custom implementation didn't really make easier for people to return custom HTTP status code depending on the errors. Again, it's hard to reason about when to set custom codes and how. Take an example what we have to do to extract the message and status code from an error before returning a response from the API:
```go
switch err.(type) {
case errcode.ErrorCode:
daError, _ := err.(errcode.ErrorCode)
statusCode = daError.Descriptor().HTTPStatusCode
errMsg = daError.Message()
case errcode.Error:
// For reference, if you're looking for a particular error
// then you can do something like :
// import ( derr "github.com/docker/docker/errors" )
// if daError.ErrorCode() == derr.ErrorCodeNoSuchContainer { ... }
daError, _ := err.(errcode.Error)
statusCode = daError.ErrorCode().Descriptor().HTTPStatusCode
errMsg = daError.Message
default:
// This part of will be removed once we've
// converted everything over to use the errcode package
// FIXME: this is brittle and should not be necessary.
// If we need to differentiate between different possible error types,
// we should create appropriate error types with clearly defined meaning
errStr := strings.ToLower(err.Error())
for keyword, status := range map[string]int{
"not found": http.StatusNotFound,
"no such": http.StatusNotFound,
"bad parameter": http.StatusBadRequest,
"conflict": http.StatusConflict,
"impossible": http.StatusNotAcceptable,
"wrong login/password": http.StatusUnauthorized,
"hasn't been activated": http.StatusForbidden,
} {
if strings.Contains(errStr, keyword) {
statusCode = status
break
}
}
}
```
You can notice two things in that code:
1. We have to explain how errors work, because our implementation goes against how easy to use Go errors are.
2. At no moment we arrived to remove that `switch` statement that was the original reason to use our custom implementation.
This change removes all our status errors from the errors package and puts them back in their specific contexts.
IT puts the messages back with their contexts. That way, we know right away when errors used and how to generate their messages.
It uses custom interfaces to reason about errors. Errors that need to response with a custom status code MUST implementent this simple interface:
```go
type errorWithStatus interface {
HTTPErrorStatusCode() int
}
```
This interface is very straightforward to implement. It also preserves Go errors real behavior, getting the message is as simple as using the `Error()` method.
I included helper functions to generate errors that use custom status code in `errors/errors.go`.
By doing this, we remove the hard dependency we have eeverywhere to our custom errors package. Yes, you can use it as a helper to generate error, but it's still very easy to generate errors without it.
Please, read this fantastic blog post about errors in Go: http://dave.cheney.net/2014/12/24/inspecting-errors
Signed-off-by: David Calavera <david.calavera@gmail.com>
|
||
|---|---|---|
| .github | ||
| api | ||
| builder | ||
| cli | ||
| cliconfig | ||
| container | ||
| contrib | ||
| daemon | ||
| distribution | ||
| docker | ||
| dockerversion | ||
| docs | ||
| errors | ||
| experimental | ||
| hack | ||
| image | ||
| integration-cli | ||
| layer | ||
| man | ||
| migrate/v1 | ||
| opts | ||
| pkg | ||
| profiles | ||
| project | ||
| reference | ||
| registry | ||
| runconfig | ||
| utils | ||
| vendor/src | ||
| volume | ||
| .dockerignore | ||
| .gitignore | ||
| .mailmap | ||
| AUTHORS | ||
| CHANGELOG.md | ||
| CONTRIBUTING.md | ||
| Dockerfile | ||
| Dockerfile.aarch64 | ||
| Dockerfile.armhf | ||
| Dockerfile.gccgo | ||
| Dockerfile.ppc64le | ||
| Dockerfile.s390x | ||
| Dockerfile.simple | ||
| Dockerfile.windows | ||
| LICENSE | ||
| MAINTAINERS | ||
| Makefile | ||
| NOTICE | ||
| README.md | ||
| ROADMAP.md | ||
| VENDORING.md | ||
| VERSION | ||
Docker: the 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 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 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 either on your computer for building applications or on servers for running them. To get started, check out the installation instructions in the documentation.
We also offer an interactive tutorial for quickly learning the basics of using Docker.
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 cgroups and namespaces capabilities of the Linux kernel
- The Go programming language
- The Docker Image Specification
- The Libcontainer Specification
Contributing to Docker 
| Master (Linux) | Experimental (linux) | Windows | FreeBSD |
|---|---|---|---|
Want to hack on Docker? Awesome! We have instructions to help you get started contributing code or documentation.
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. 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.
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.
We are always open to suggestions on process improvements, and are always looking for more maintainers.
Talking to other Docker users and contributors
| Internet Relay Chat (IRC) |
IRC is a direct line to our most knowledgeable Docker users; we have
both the |
| Google Groups | There are two groups. Docker-user is for people using Docker containers. The docker-dev group is for contributors and other people contributing to the Docker project. |
| You can follow Docker's Twitter feed to get updates on our products. You can also tweet us questions or just share blogs or stories. | |
| Stack Overflow | Stack Overflow has over 7000 Docker questions listed. We regularly monitor Docker questions and so do many other knowledgeable Docker users. |
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 https://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.
- Docker Registry: Registry server for Docker (hosting/delivery of repositories and images)
- Docker Machine: Machine management for a container-centric world
- Docker Swarm: A Docker-native clustering system
- Docker Compose (formerly Fig): Define and run multi-container apps
- 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. Add your project there.