Dockerization

I've made a basic Dockerfile for use with Docker and tested out automated builds on hub.docker.com.

I don't have the ipython namespace registered (as specified in the new README here). If you want to check out what I've done, I created [`rgbkrk/nbviewer-docker-trial` on registry.hub.docker.com](https://registry.hub.docker.com/u/rgbkrk/nbviewer-docker-trial/). It currently tracks this `dockerization` branch.

To try it out, run:

```
$ docker pull rgbkrk/nbviewer-docker-trial
$ docker run -d -p 8080:8080 rgbkrk/nbviewer-docker-trial # Port on host:port on container
```

Add environment variables for the container by appending `-e KEY=VALUE`. Example:

```
$ docker run -d -p 8080:8080 rgbkrk/nbviewer-docker-trial -e 'GITHUB_OAUTH_KEY=YOURKEY' \
                                                       -e 'GITHUB_OAUTH_SECRET=YOURSECRET'
```

Note that the `-d` command will run it as a daemon, which means you won't see STDOUT. Take away the `-d` to see the logs flow by. To terminate the running instance, you'll need to open a terminal on the same box and list all the running containers:

```
docker ps
```

then kill the container by its ID

```
docker kill <container_id>
```

Example termination:

```
core@core03 ~ $ docker ps
CONTAINER ID        IMAGE                                 COMMAND                CREATED             STATUS              PORTS                    NAMES
0d8cf981266f        rgbkrk/nbviewer-docker-trial:latest   /bin/sh -c 'python -   6 seconds ago       Up 6 seconds        0.0.0.0:8080->8080/tcp   romantic_archimedes
core@core03 ~ $ docker kill 0d
0d
```

My thought here is to actually switch from salt-states & pillars etc. to just *the CoreOS way* ™. If a node goes down, the containers get shifted over to another host to shift the workload. This will all be done via [fleet](https://github.com/coreos/fleet) in production. For development, we'll be letting people run with one Docker container. I'll be linking these to a shared memcached container as well.

Remaining steps:

* [X] Create a base Dockerfile
* [X] Register the IPython and Jupyter namespaces on hub.docker.com

Optional steps (later revision, separate repositories?):
* [x] Create the systemd init files for fleet
* [X] Determine how this should interface with load balancers
* [X] Create a memcached service to link to (not as important in this iteration)