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<!-- [metadata]>
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title = "Run a simple application"
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description = "Learn how to manage and operate Docker containers."
keywords = ["docker, the docker guide, documentation, docker.io, monitoring containers, docker top, docker inspect, docker port, ports, docker logs, log, Logs"]
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parent="smn_containers"
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weight=-5
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<![end-metadata]-->
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# Run a simple application
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In the ["*Hello world in a container*" ](dockerizing.md ) you launched your
first containers using the `docker run` command. You ran an *interactive container* that ran in the foreground. You also ran a *detached container* that ran in the background. In the process you learned about several Docker commands:
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* `docker ps` - Lists containers.
* `docker logs` - Shows us the standard output of a container.
* `docker stop` - Stops running containers.
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## Learn about the Docker client
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If you didn't realize it yet, you've been using the Docker client each time you
typed `docker` in your Bash terminal. The client is a simple command line client
also known as a command-line interface (CLI). Each action you can take with
the client is a command and each command can take a series of flags and arguments.
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# Usage: [sudo] docker [subcommand] [flags] [arguments] ..
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# Example:
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$ docker run -i -t ubuntu /bin/bash
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You can see this in action by using the `docker version` command to return
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version information on the currently installed Docker client and daemon.
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$ docker version
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This command will not only provide you the version of Docker client and
daemon you are using, but also the version of Go (the programming
language powering Docker).
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Client:
Version: 1.8.1
API version: 1.20
Go version: go1.4.2
Git commit: d12ea79
Built: Thu Aug 13 02:35:49 UTC 2015
OS/Arch: linux/amd64
Server:
Version: 1.8.1
API version: 1.20
Go version: go1.4.2
Git commit: d12ea79
Built: Thu Aug 13 02:35:49 UTC 2015
OS/Arch: linux/amd64
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## Get Docker command help
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You can display the help for specific Docker commands. The help details the
options and their usage. To see a list of all the possible commands, use the
following:
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$ docker --help
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To see usage for a specific command, specify the command with the `--help` flag:
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$ docker attach --help
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Usage: docker attach [OPTIONS] CONTAINER
Attach to a running container
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--help Print usage
--no-stdin Do not attach stdin
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--sig-proxy=true Proxy all received signals to the process
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> **Note:**
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> For further details and examples of each command, see the
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> [command reference](../reference/commandline/cli.md) in this guide.
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## Running a web application in Docker
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So now you've learned a bit more about the `docker` client you can move onto
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the important stuff: running more containers. So far none of the
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containers you've run did anything particularly useful, so you can
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change that by running an example web application in Docker.
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For our web application we're going to run a Python Flask application.
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Start with a `docker run` command.
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$ docker run -d -P training/webapp python app.py
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Review what the command did. You've specified two flags: `-d` and
`-P` . You've already seen the `-d` flag which tells Docker to run the
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container in the background. The `-P` flag is new and tells Docker to
map any required network ports inside our container to our host. This
lets us view our web application.
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You've specified an image: `training/webapp` . This image is a
pre-built image you've created that contains a simple Python Flask web
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application.
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Lastly, you've specified a command for our container to run: `python app.py` . This launches our web application.
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> **Note:**
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> You can see more detail on the `docker run` command in the [command
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> reference](../reference/commandline/run.md) and the [Docker Run
> Reference](../reference/run.md).
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## Viewing our web application container
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Now you can see your running container using the `docker ps` command.
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$ docker ps -l
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CONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES
bc533791f3f5 training/webapp:latest python app.py 5 seconds ago Up 2 seconds 0.0.0.0:49155->5000/tcp nostalgic_morse
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You can see you've specified a new flag, `-l` , for the `docker ps`
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command. This tells the `docker ps` command to return the details of the
*last* container started.
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> **Note:**
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> By default, the `docker ps` command only shows information about running
> containers. If you want to see stopped containers too use the `-a` flag.
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We can see the same details we saw [when we first Dockerized a
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container](dockerizing.md) with one important addition in the `PORTS`
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column.
PORTS
0.0.0.0:49155->5000/tcp
When we passed the `-P` flag to the `docker run` command Docker mapped any
ports exposed in our image to our host.
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> **Note:**
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> We'll learn more about how to expose ports in Docker images when
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> [we learn how to build images](dockerimages.md).
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In this case Docker has exposed port 5000 (the default Python Flask
port) on port 49155.
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Network port bindings are very configurable in Docker. In our last example the
`-P` flag is a shortcut for `-p 5000` that maps port 5000 inside the container
to a high port (from *ephemeral port range* which typically ranges from 32768
to 61000) on the local Docker host. We can also bind Docker containers to
specific ports using the `-p` flag, for example:
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$ docker run -d -p 80:5000 training/webapp python app.py
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This would map port 5000 inside our container to port 80 on our local
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host. You might be asking about now: why wouldn't we just want to always
use 1:1 port mappings in Docker containers rather than mapping to high
ports? Well 1:1 mappings have the constraint of only being able to map
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one of each port on your local host.
Suppose you want to test two Python applications: both bound to port 5000 inside
their own containers. Without Docker's port mapping you could only access one at
a time on the Docker host.
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So you can now browse to port 49155 in a web browser to
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see the application.
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![Viewing the web application ](webapp1.png ).
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Our Python application is live!
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> **Note:**
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> If you have been using a virtual machine on OS X, Windows or Linux,
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> you'll need to get the IP of the virtual host instead of using localhost.
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> You can do this by running the `docker-machine ip your_vm_name` from your command line or terminal application, for example:
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>
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> $ docker-machine ip my-docker-vm
> 192.168.99.100
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>
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> In this case you'd browse to `http://192.168.99.100:49155` for the above example.
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## A network port shortcut
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Using the `docker ps` command to return the mapped port is a bit clumsy so
Docker has a useful shortcut we can use: `docker port` . To use `docker port` we
specify the ID or name of our container and then the port for which we need the
corresponding public-facing port.
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$ docker port nostalgic_morse 5000
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0.0.0.0:49155
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In this case you've looked up what port is mapped externally to port 5000 inside
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the container.
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## Viewing the web application's logs
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You can also find out a bit more about what's happening with our application and
use another of the commands you've learned, `docker logs` .
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$ docker logs -f nostalgic_morse
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* Running on http://0.0.0.0:5000/
10.0.2.2 - - [23/May/2014 20:16:31] "GET / HTTP/1.1" 200 -
10.0.2.2 - - [23/May/2014 20:16:31] "GET /favicon.ico HTTP/1.1" 404 -
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This time though you've added a new flag, `-f` . This causes the `docker
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logs` command to act like the `tail -f` command and watch the
container's standard out. We can see here the logs from Flask showing
the application running on port 5000 and the access log entries for it.
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## Looking at our web application container's processes
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In addition to the container's logs we can also examine the processes
running inside it using the `docker top` command.
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$ docker top nostalgic_morse
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PID USER COMMAND
854 root python app.py
Here we can see our `python app.py` command is the only process running inside
the container.
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## Inspecting our web application container
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Lastly, we can take a low-level dive into our Docker container using the
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`docker inspect` command. It returns a JSON document containing useful
configuration and status information for the specified container.
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$ docker inspect nostalgic_morse
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You can see a sample of that JSON output.
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[{
"ID": "bc533791f3f500b280a9626688bc79e342e3ea0d528efe3a86a51ecb28ea20",
"Created": "2014-05-26T05:52:40.808952951Z",
"Path": "python",
"Args": [
"app.py"
],
"Config": {
"Hostname": "bc533791f3f5",
"Domainname": "",
"User": "",
. . .
We can also narrow down the information we want to return by requesting a
specific element, for example to return the container's IP address we would:
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$ docker inspect -f '{{range .NetworkSettings.Networks}}{{.IPAddress}}{{end}}' nostalgic_morse
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172.17.0.5
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## Stopping our web application container
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Okay you've seen web application working. Now you can stop it using the
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`docker stop` command and the name of our container: `nostalgic_morse` .
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$ docker stop nostalgic_morse
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nostalgic_morse
We can now use the `docker ps` command to check if the container has
been stopped.
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$ docker ps -l
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## Restarting our web application container
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Oops! Just after you stopped the container you get a call to say another
developer needs the container back. From here you have two choices: you
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can create a new container or restart the old one. Look at
starting your previous container back up.
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$ docker start nostalgic_morse
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nostalgic_morse
Now quickly run `docker ps -l` again to see the running container is
back up or browse to the container's URL to see if the application
responds.
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> **Note:**
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> Also available is the `docker restart` command that runs a stop and
> then start on the container.
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## Removing our web application container
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Your colleague has let you know that they've now finished with the container
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and won't need it again. Now, you can remove it using the `docker rm` command.
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$ docker rm nostalgic_morse
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Error: Impossible to remove a running container, please stop it first or use -f
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What happened? We can't actually remove a running container. This protects
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you from accidentally removing a running container you might need. You can try
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this again by stopping the container first.
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$ docker stop nostalgic_morse
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nostalgic_morse
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$ docker rm nostalgic_morse
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nostalgic_morse
And now our container is stopped and deleted.
> **Note:**
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> Always remember that removing a container is final!
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# Next steps
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Until now you've only used images that you've downloaded from Docker Hub. Next,
you can get introduced to building and sharing our own images.
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Go to [Working with Docker Images ](dockerimages.md ).