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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There’s a lot of buzz stating that Cloud Computing and Big Data are synonymous. See a Forbes article here stating that ”
“Big data is the new cloud computing.”
This sentiment was recently expressed in an interview with Motley Fool analyst Tim Beyers, who analyzed the zeitgeist coming out of the South-by-Southwest (SXSW) conference and observed that cloud computing and big data were now one in the same phenomena, converging on enterprises of all shapes and sizes.”
For those who don’t know what big data is, this Intel Video gives you a “Big Data 101” primer.
The Cloud definitely provides a cost effect and timely way to go after big data problems and then using the elasticity of the cloud’s IaaS foundation, dump the costly resources when you’ve finished or allow them to grow only when needed. But they are not one and the same. Big Data is just the current “Bell of the ball” for enterprise usage of the Cloud. See below Gartner’s Hype Cycle for emerging technologies 2012. This shows we are either in or approaching the “Trough of Disillusionment” regarding Reduce Map and the offerings of DBSaaS. I’m eager to apply some innovative ideas I have regarding the trip out of this trough on some upcoming projects.
The dramatic growth in smartphone, tablet and vertical market portable devices e.g., medical instrumentation is starting to drive major change at big tech companies. If you watch product offerings and new positioning of Google, Microsoft, and Apple, you’ll see that significant investments are geared toward the mobile consumer and mobile information worker. These products require new device technologies such as flexible silicon and Thin flexible substrates for interconnect technology.
A good example of this is the lighting fast reorganization of Intel after Brian Krzanich’s installation as CEO. Under Otellini’s tenure Intel missed a huge opportunity to become the chip supplier to Apple for iPhones even though the traditional conservative “number crunching/data driven” advice given to Paul Otellini went against his gut, Intel passed on the opportunity. Their analysis misjudged the potential volume by a factor of 100 and over estimated the costs of manufacturing. Basically the conservative mindset of “group think” there projected the iPhone as a losing business proposition. See here The new CEO has immediately reorganized the global enterprise to make it more agile and created a New devices Group reporting directly to him. See here
Hopefully this will open Intel up to address new markets and new types of Si architecture along with manufacturing processes. Also the industry will hopefully follow Intel’s lead and innovate even more in this hot technology domain When you look at flexible silicon and thin film technologies, the future is clear. New companies will grow to tech giants that embrace this technology and benefit from lessons learned from the old tech giants.
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.
My Conclusion on Si Architecture Trends and thier ecosystem impact
Today’s Si companies must track the key trends in Si technology development, assembly test, Nanotechnology, Cooling, Emerging Research, Virtualization, acceleration and Si Complex Architectures to help drive their product teams in close collaboration with other Si vendors to keep the enterprise in a thought leadership position contemporary with the Silicon Industry along with consumer demands.
This blog is intended to document key technology trends and issues I feel will have a major impact betwen now and 2035. The following areas will be covered:
Silicon technology, architecture processes and innovation
| TREND | EXAMPLE |
| Integration Level | Components/Chip, Moore’s Law |
| Cost | Cost Per Function |
| Speed | Microprocessor Throughput |
| Power | Laptop or Cell Battery Life |
| Compactness | Small and Light-weight Products |
| Functionality | Nonvolatile Memory, Imager |
Software As a Service
Cloud Computing SW & HW trends to watch
System Architecture
Enterprise IT Architecture
Applications Infrastructure as it relates to all of the above.