[WIP] Indexing

This is the beginning of notebook indexing in support of search (#252).

Currently I'm making an opinionated view on *how* we learn about an elasticsearch node, configured here through Docker provided environment variables (`NBSEARCH_PORT`). The linked elasticsearch node then needs to be named `nbsearch` to be picked up. In concert with the memcaching layer then, our `docker run` line looks like:

```
docker run --name nbviewer.1.service -p 8080:8080 \
           --link nbcache:nbcache \
           --link nbsearch:nbsearch \
           ipython/nbviewer
```
This is what a response looks like:

```
In [20]: resp = es.index(index='notebooks', doc_type='ipynb', body=nb_contents, id=notebook_id)

In [21]: resp
Out[21]:
{u'_id': u'88fa5926-59d7-5c13-ab4a-ea0e798a36e8',
 u'_index': u'notebooks',
 u'_type': u'ipynb',
 u'_version': 1,
 u'created': True}
```

I should at the very least log whether or not this was created. Not sure what else should be captured.