Let's have a look at some of the technology lexicon associated with Cloud Architectures.

BigTable

Cloud database offered by Google. It is non-relational and highly scalable.

Cloud computing

There are five principles of cloud computing
1. Resources are pooled
2. Machines are virtualised (achieves maximum utilisation)
3. Elasticity. Users can scale up or down very easily.
4. Virtual machines can be created or deleted automatically
5. Billing is by resource usage rather than by a flat fee

CloudBursting

Cloudbursting concerns hybrid architectures where a classical enterprise architecture can make use of a cloud on demand. This means that part of the architecture can be behind a private firewall and be kept away from the cloud completely but the elastic benefits of the cloud are still possible should periodic or unexpected traffic occur. In the cloud bursting model, the load balancer is not in the cloud. The load balancer decides when to use the cloud based on demand and traffic.

Commodity computers

Commodity computers are cheaper computers used in architectures which do not require the hardware to be highly reliable. This is usually possible when the software has a high degree of failover incorporated. Google's MapReduce framework uses commodity computers and then reassigns tasks if any of the commodity computers fail and do not finish allocated tasks.

Data centre

The physical home which stores all computational resources
Facebook has various data centres in the US see:
http://www.datacenterknowledge.com/the-facebook-data-center-faq/

Infrastructure as a Service (IaaS)

This is the lowest level of service available from a Cloud. In this case, the Cloud provider simple provides virtual machine images with an operating system. Amazon's EC2 is an example of IaaS.

Hypervisor (also called virtual machine manager)

A thin layer of software that allocates hardware resources dynamically and transparently to virtual machines. The term hypervisor was coined as an evolution of the term "supervisor," the software that provided control on earlier hardware.

Platform as a service (PaaS)

Allows users to create their own application using the Cloud provider's platform and tools. This allows rapid development but also means there is a risk of vendor lock-in.

Example: Google's AppEngine, Microsoft's Azure, force.com

SimpleDB

Cloud database offered by Amazon. It is non-relational and highly scalable.

Sharding

Sharding is based on the "shared-nothing" principle. There are no dependencies between different portions of data. To achieve this usually involves denormalising data so that dependent data is stored together. The result is parallel processing of independent data is possible and hence higher concurrency is possible.

Data can also then be partitioned very easily. This is usually done horizontally - splitting up rows into separate partitions. Each individual partition is referred to as a shard or database shard. Partitioning data means the total number of rows in each table is reduced. This reduces index size, which generally improves search performance.

Software as a service (SaaS)

Allows users to run existing online applications.

Example: Salesforce.com, pixlr.com, jaycut.com

Private Cloud

In this model there are no subscribing customers, the computing resources are controlled by a single organisation. But, the resources are still pooled and shared; machines are still virtualised. The difference between the private cloud and standard virtualisation is that in the private cloud model, the virtual machine creation and deletion can be automated and can achieved very quickly and thus elastic scaling characteristics that are associated with cloud computing that can't be with standard virtualisation can be achieved.

References:

1. Google AppEngine http://en.wikipedia.org/wiki/Appengine
2. Google's map reduce http://en.wikipedia.org/wiki/Mapreduce
3. The Cloud at your Service, Jothy Rosenbery, Arthur Mateos (Manning).

Source: http://dublintech.blogspot.com/2011/06/cloudspeak.html