I still remember the time when the first CD players came out in the mid 80s. By the mid 90s vinyl had virtually disappeared from the shelves. Same with the Flatscreen TVs. In this case it went a couple of years faster until the CRTs had been virtually wiped out around 2010-2012.–“Nothing is as powerful as an idea whose time has come”.
Although I am apparently a big believer in Computing Clouds, I do not observe a similar wipe out of traditional enterprise IT and data centers (yet). When I look around at technology in general, the trend seems to be even the opposite: decentralization instead of centralization. For example:
Pretty stiff arguments against centralization.
So where are computing clouds? What could be wrong with them?–I believe they oversaw the data. In the year 2011, McCrory described an a meanwhile famous Blog Post the qualitative characteristics of data that he called ”Data Gravity”.
”Data Gravity” is a metaphor describing the economics of data, demanding data to better stay where it is and to not to ship it around, no matter how big or small the amount of data may be. A finding that is supported by Jim Gray who stated that compared to the cost of moving data, everything else would be negligible (in D. Patterson, “A conversation with jim gray,” ACM Queue, vol. 1, no. 4, pp. 53–56, 2003). As consequence, McCrory states that data must have something that is comparable to a gravitational pull that pulls services and applications to it rather than the other way around: ”Data Gravity”.
This blends with the Map Reduce programming model where computation, for example batch jobs written in Java or Python, are brought close to the data rather than the other way around. Under the assumption that ”Data Gravity” exists it seems reasonable to question whether computing clouds, that centralize and rationalize resources for computation, that are seemingly mobile, are the landmark innovation that is required to wipe out inefficient onsite data centers. This is further amplified by the ever increasing number of powerful heterogenous mobile devices.
Disregarding data gravity, there are of course many more issues around data, such as data residency, privacy, confidentiality and so on … .
The alternatives to computing clouds, onsite data centers, do not seem to go away as quickly as everyone had hoped three years ago. Recently also Microsoft chosen to ‘renew’ their ‘strong’ commitment to Sharepoint Server. –For now.
Read Complimentary Relevant Research
How to Create a Data Strategy for Machine Learning-Powered Artificial Intelligence
MLpAI can help deliver systems with more automation and less human intervention, but success requires a data strategy to deal with the...
View Relevant Webinars
Big Data Architectures: Comparing Relational and NoSQL Databases
In the big data arena, few choices are more important and impactful than the persistent data store. Relational and nonrelational databases...
Comments or opinions expressed on this blog are those of the individual contributors only, and do not necessarily represent the views of Gartner, Inc. or its management. Readers may copy and redistribute blog postings on other blogs, or otherwise for private, non-commercial or journalistic purposes, with attribution to Gartner. This content may not be used for any other purposes in any other formats or media. The content on this blog is provided on an "as-is" basis. Gartner shall not be liable for any damages whatsoever arising out of the content or use of this blog.