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+=================================
+Data Broker Service Layer Design
+=================================
+
+Motivation
+==========
+
+Databroker has been actively developed and widely used over the past 2 years. 
+It has become more powerful and stable thanks to Dan Allan's efforts over the
+past year. Its stability and wide acceptance as the de facto way access data
+acquired in our beamlines. A new wave of requirements are reported as a result
+of our community outreach. One of these requirements is a set of databroker
+server implementations that will allow remote access to experimental data over
+network. The service layer will also eliminate any issues that may occur as a
+result of providing direct/library-level access to databases, allowing 
+us to implement data access policies.
+
+Challenges
+===========
+
+NSLS-II and other facilities have a wide variety of experimental setups that
+generate data at different rates and structure. This poses a major challenge
+for a single-backend implementation. Another challenge is the lack of sys admin
+and dev-ops support. Making performant and reliable asynchronous servers with 
+low-latency is that are maintainable in the long term that are easy to deploy
+is especially difficult with the amount of resources at hand.
+
+
+Roadmap
+===========
+
+- Identify the data rates required to be transferred in NSLS-II databases. This
+does not require a major effort, a simple investigation of existing metadatastore
+and filestore will suffice
+
+- Identify the technologies to be used for transmitting ND arrays over the wire:
+  msgpack, protobuffe, h5serv, etc. This includes performance measurements 
+
+- Have a first cut on existing databroker using .. _ujson: http://artem.krylysov.com/blog/2015/09/29/benchmark-python-json-libraries/
+
+- Prioritize the backends to be implemented, define timelines, and implement.
+
+- Add an authentication layer
+
+
+Technology
+=============
+
+Given there are plans for central storage and data management, the implementation
+of the server layer must be scalable. This means a micro-service oriented
+infrastructure that can eventually be placed behind load balancers is a good
+intuitive choice. A fully RESTful approach is achiveable yet limiting given the
+flexibility provided by the stack. This layer needs some discussion. We could
+definitely adopt a RESTful approach (ugh, dreaded approach word) could be
+adopted rather than handler per document type sort of approach of metadataservice
+and amostra.
+
+Server Side Design
+===================
+
+HeaderHandler
+------------
+
+**get:** Decode jsonified query and return a serialize a list of dicts
+If invalid request, return appropriate http error code.
+
+
+EventSourceHandler
+------------------
+
+**get:** Using the uid of the descriptor(s), obtains an event generator.
+By paginating on this generator, returns the payload to the client side.
+In the future, this bit will sort out the source of the data fill source
+and redirect to the appropriate handler. In this context, handler refers to
+the eventsource provided specific choice of technology given the data structure
+and rate.