Cloud Computing Architectures: Scalability vs. Elasticity

For Cloud Solutions, Scalability and Elasticity are key requirements. In private Cloud Solutions, this should also be supported, even if scalability and elasticity might has a lower border as we see in the public Cloud. Scaling applications means that we can add a new instance of Linux or a Windows Server. Elasticity is something “more advanced” to that as described by Reuven Cohen, an opinion leader in Cloud Computing (Cohen, 2010). Reuven describes scalability as the possibility to “grow to the demands of the users on a platform” whereas he states that elasticity is something that reflects real-time conditions. A platform might have millions of users, but if this platform is only available in the United States, there might be significant fewer load on the servers during night. The load will be much higher at peak times and elasticity means that unnecessary instances are shut down if the load is lower or that new instances are started if the load is higher. (Owens, 2010) defines Elasticity as „the golden nugget of Cloud Computing“ and a key inhibitor to move to Cloud Environments. A very similar definition on what Cohen defined as elasticity is also provided by the National Institute of Standards and Technology  (Mell & Grance , 2011):
 

“Capabilities can be elastically provisioned and released, in some cases automatically, to scale rapidly outward and inward commensurate with demand. To the consumer, the capabilities available for provisioning often appear to be unlimited and can be appropriated in any quantity at any time.” –  (Mell & Grance , 2011)

Elasticity is something that can lower costs, but requires a lot of up-front work. Elasticity has to be supported by the software architecture and resource automation has to be put in place.

Picture Copyright by Moyan Brenn