To get some insight into the mind of the CIO, some information from Gartner summarized here and some more here. The there is the IBM Global CIO Study which is a little more nebulous.
The “big levers” are the things a CIO (and their advisors) have determined are needed to meet the drivers for business. Obviously, depending on your industry, risk profile, pain points, these may vary, but there are some common themes.
As an example, some discussions with customers over the last year the conversation looks something like a matrix of needs and solutions (below). You pick you pain and then consider the relevant “levers” (solutions).
There is no doubt that cloud is present in the mind of CIO’s around the world and it is assured a place in the future of the IT industry. Given the volume of marketing behind the term “cloud” and the scarcity of practical case studies, most of the time is spent discussing cloud, its definition, and its position on the “Gartner hype cycle”. The 2010 version (right) shows Cloud cresting the wave of “Inflated Expectations” and heading down into the “Trough of Disillusionment”. This point in the hype cycle is a good indicator of the level of cloud adoption. This is often the point where early adopting mainstream IT has finished the initial discovery/trials and is starting to think practically in terms of implementation.
My conclusion as to whether Cloud Computing is a “big level” is: NO
Not today, but maybe in the very near future. It’s just not yet a systemic answer to a quantifiable problem. The only thing between here and the day when it will be an entrenched part of the Enterprise CIO toolbox is the passing of time. Lots of things can impact the amount of time it takes..
So when is the next wave of cloud computing ?
You can also consider this from the perspective of the Rogers curve.
It is generally accepted that cloud is a innovative and emerging technology. Using Rogers curve we probably sit in the early adopters phase with the early majority now considering cloud. These early majority and even more so the late majority will be traditional enterprise customers and are the next wave of cloud adoption. This wave will large, it represents the largest IT spend. It will deliver a transformation of cloud solutions from high valuations, to high actual value. This will be evidenced by industry consolidation through acquisition and hopefully a new independent software vendor (ISV) or two just as open source delivered us RedHat.
What defines how fast we progress across this curve can be explained using Rogers 5 factors;
Relative Advantage – How improved an innovation is over the previous generation?
Whats the size of the pull towards using this innovation. The area of biggest debate. Is it evolution or revolution ? The marketing is trying to push the “revolution” angle. Not sure enterprises are buying that at this point. This may be because of lack of understanding, lesser pressure for agility compared to cost or a number of factors.
Compatibility – The level of compatibility that an innovation has to be assimilated into an individual’s life.
For enterprises this needs to be true for operations, engineering and management. Not a big leap for a engineer to assimilate cloud architecture concepts, but it is a bigger leap for the decision makers to make. Impacts across an IT organization spans power bases (ops vs. dev), which makes this more complicated.
Complexity – If the innovation is too difficult to use an individual will not likely adopt it.
Certainly the “ease of use” aspect of the technology is non-trivial at this point and will develop over time ahead of enterprise adoption. Open API based architecture is helping, but general UI immaturity is a barrier. Also completeness of integration between components needed for a “complete” solution is immature. The biggest barrier in this space however is probably the organization components; security fears, abstraction of BU’s from infrastructure, dev/ops role transformation, asset financial management changes etc… etc..
Trialability - How easily an innovation may be experimented with as it is being adopted.
If a user has a hard time using and trying an innovation this individual will be less likely to adopt it. Lots of open source, and downloadable components. Key focus of most of the vendors in this space. Hardware is a commodity, so resources are fairly easy to come by for PoC.
Observability – The extent that an innovation is visible to others.
An innovation that is more visible will drive communication among the individual’s peers and personal networks and will in turn create more positive or negative reactions. A definite weak point for cloud at the moment. The secrecy of public vendors and customers alike is hindering. Some of the bad press of April 21 has put this backwards a little bit, but also freed up alot of companies to talk about cloud experiences.
So for an enterprise CIO, when is the right time to paddle out and try to catch the “next wave of cloud computing”
The answer is “depends”.. A bit of a anti-climax for sure.
The only common answer to “when to adopt cloud computing architectures” is to “implement based on value“.
If you have a need or business driver. Consider if some aspect of cloud computing architecture can provide the solution, and then implement. Make sure the return for the project investment is short-term (2-3 years). Use only technologies that provide open API interfaces to make sure you integration and customization can be ported to a new platform in the future.
Contributed by: Brad Vaughan