OpenCluster is a suite of products to give applications the ability to co-ordinate work with each other (cluster locks), communicate 
with each other (message queues) and share data with each other (clustered data).

OpenCluster Locks
	
	This product allows applications to co-ordinate work that would conflict with each other.  For example, if the process only
	allows for one new account to be created at a time, then you might have a 'new account' lock.  Whenever a process needs to
	create a new account, it sets that lock, and if another process needs to create a new account, it will attempt to set the lock
	also but will have to wait until the first process releases it.  Once released, the second process can receive the lock,
	process and when done, release it.

OpenCluster Messaging

	This product provides a mechanism where different processes can send and receive work items amongst each other.  For example, a
	process might need a new account to be created.  It sends a message to the 'accounts' process asking for a new account to be
	created.  One or more 'accounts' processes might be running, and one will receive the request, process it, and return a reply
	with the relevant details.

OpenCluster Cache

	This product provides a simple distributed Hashtable that is used as a cache.  Permenant data should not be used on it, instead
	this is a cache to hold data that is more costly to produce.  For example, it might be the rendered output of a webpage.  The
	key will contain certain variables that make up that page, and when those variables change, the rendered output changes.  But
	if the variables are the same, then dont need to spend time rendering the page, but instead provide the cached output.  Cached
	items can have an expiry... so that they automatically dissapear after a certain time.  Also, there can be limits on the amount
	of memory to dedicate to the cache, and when the cache gets full, start removing the items that havent been used for the
	longest.

OpenCluster Data (Simple)

	This product provides a simple distributed key/value hash table.  It is distrubuted amongst the nodes and clients simply set
	string based keys with string or integer based values.  Very similar to OpenCluster-Cache, but the data is meant to be less
	volatile.

OpenCluster Data (Structured)

	This product provides a much more advanced and structured storage solution.  It provides a far more flexible solution to 
	looking up data, with the premise being that a properly designed and implemented system, should be able to pull out all the 
	information it needs in a single request.  To accomplish this, it uses a concept similar to database tables, but instead of 
	each table having defined columns, each table instead has rows with an undefined number of cells, and each cell is labeled.  
	For example, you can have 'Users' row that might have a bunch of values 
		'userID=5454, fullname="Joe Bloggs", email="wherever@example.com"'.  
	Queries could be performed on any of those cells to return the row (or rows).  Additionally this means that you dont need empty 
	cells.  Each row can use only the cells that it wants to populate.

OpenCluster Blocks

	This product is a bit more technical in nature.  Very similar to the SimpleData product but instead of providing a key/value
	where the value is some arbitrarily sized value, with Clustered Blocks, you are instead dealing with blocks of memory that are
	distributed across a system.  Different languages provide different mechanisms, and some languages may be very difficult to
	implement.  Essentially, if an application wants to store some data, it opens the block, stores data in it, and commits it.
	Very simimilar in functionality behind the scenes, but very different implementation and design analogy from the client
	perspective.




All products should be multi-tenantable, meaning that you could have multiple customers or users on the one system, neither conflicting 
or even aware of each other.  This could be for seperation of processing, or it could be to provide a service to multiple customers.