Architecture.md Enable deep links - point to Swagger etc. (#114)

* Enable deep links - point to Swagger etc.

* .com fix and Quickstart sample data mention

docs/architecture.md

@@ -3,17 +3,24 @@
 The following diagram shows the overall architecture for Amundsen.
 ![](img/Amundsen_Architecture.png)
 
+## Frontend
 The frontend service serves as web UI portal for users interaction. 
 It is Flask-based web app which representation layer is built with React with Redux, Bootstrap, Webpack, and Babel.
 
-The search service leverages Elasticsearch's search functionality and 
-provides a RESTful API to serve search requests from the frontend service. 
+## Search
+The [search service](https://github.com/lyft/amundsensearchlibrary#amundsen-search-service) proxy leverages Elasticsearch's search functionality (or Apache Atlas's search API, if that's the backend you picked) and 
+provides a RESTful API to serve search requests from the frontend service. This [API is documented and live explorable]() through OpenAPI aka "Swagger".
 Currently only [table resources](https://github.com/lyft/amundsendatabuilder/blob/master/databuilder/models/elasticsearch_document.py) are indexed and searchable.
-The search index is built with the [elasticsearch publisher](https://github.com/lyft/amundsendatabuilder/blob/master/databuilder/publisher/elasticsearch_publisher.py).
+The search index is built with the [databuilder elasticsearch publisher](https://github.com/lyft/amundsendatabuilder/blob/master/databuilder/publisher/elasticsearch_publisher.py).
 
-The metadata service currently uses a Neo4j proxy to interact with Neo4j graph db and serves frontend service's metadata. 
+## Metadata
+The [metadata service](https://github.com/lyft/amundsenmetadatalibrary#amundsen-metadata-service) currently uses a Neo4j proxy to interact with Neo4j graph db and serves frontend service's metadata. 
 The metadata is represented as a graph model:
 ![](img/graph_model.png)
-The above diagram shows how metadata is modeled in Amundsen. 
+The above diagram shows how metadata is modeled in Amundsen.
+
+## Databuilder
 Amundsen provides a [data ingestion library](https://github.com/lyft/amundsendatabuilder) for building the metadata. At Lyft, we build the metadata once a day 
-using an Airflow DAG([example](https://github.com/lyft/amundsendatabuilder/blob/master/example/dags/sample_dag.py)).
+using an Airflow DAG ([example](https://github.com/lyft/amundsendatabuilder/blob/master/example/dags/sample_dag.py)).
\ No newline at end of file
+
+In addition to "real use" the databuilder is also employed as a handy tool to ingest some ["pre-cooked" demo data](https://github.com/lyft/amundsendatabuilder/blob/master/example/sample_data/) used in the Quickstart guide. This allows you to have a supersmall sample of data to explore so many of the features in Amundsen are lit up without you even having to setup connection to databases etc. to ingest real data.