It seems that that is the case. In fact the old-style justifications for on site servers and attendant OpEx costs don’t seem to make sense any more. Read this interesting article Is the data center in the Cloud or is the Cloud in the data center?
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It seems that that is the case. In fact the old-style justifications for on site servers and attendant OpEx costs don’t seem to make sense any more. Read this interesting article Is the data center in the Cloud or is the Cloud in the data center?
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This is a very interesting slide deck on Internet Trends. Specifically when you dissect digital media into audio, photo, video and audio you see we are just at the beginning of a huge growth in demand for Cloud Services to support our digital lifestyle. When you combine what we want digitally with how we use it and socialize using it, the volume of digital content will grow at an unbelievable rate through 2035. internettrends052913final-130529094939-phpapp02
The IaaS and PaaS cloud models allow architects to decouple components of an application or enterprise system into the lowest functional components and design for failure how these pieces can be utilized as “independent black boxes” to form an application. This allows for provisioning elasticity and resiliency of individual components and their states in the inevitable event of hardware or software failure.
One of the least understood impacts of this approach is that the message queues used by components can become the most important elements in assuring availability, scalability and ultimate reliability. In essence the messaging infrastructure components become the most critical parts of an applications infrastructure designed to exploit elasticity. If you envision these Enterprise Apps as complex organisms, then the message queues and their reliability become mission critical organs of the living, agile enterprise architecture. Components such as controller apps, databases and such should be isolated allowing buffering of request along with replies making the network of components more durable and state independent facilitating failover and scalability.
The influx of companies trying to exploit “Big Data” as a new revenue source has provided a number of workforce challenges for senior managers. Do they hire very smart math folk to devise new algorithms and create a “secret sauce” for their products? Do they develop or acquire superiors hardware that leverages new Si technology to better process big data? Do they form teams that have practical business experience to ferret out which real problems exist in the marketplace and what approach to analytics will be truly appreciated by customers’ end users?
Well the answer is … a little of each! The most important thing many companies are missing today is that they focus on the technology and technologist in their hiring decisions but not the business logic experience. There is great value in having teams of technology folk embedded with thought leadership coming from experience. Bright, eager, smart people, with minimal experience know theory and math but don’t know human behavior in business. They also don’t have the understanding of the technology assimilation hurdles that form huge barriers to rapid adoption and market share growth. The targeted customer base will often need help understanding:
The bottom line is an integrated team of smart technologist stewarded through development with experienced thought leadership will result in the “BIG THEORY” required to make big data solutions palatable and easily digested by the human organism we call an enterprise. Where in reality, meaningful mobile visualization transforms BIG DATA into actionable information.