Cloud computing is now entering adolescent. With all the early adopters now swimming in the cloud pool with that “I told you so” smug, fast followers are just barely beating the early majority. The gold rush to cloud is also driving the IT herd to get cloud computing training. Training vendors from multi-billion dollar behemoths to little Mom and Pop shops are ready to cash in with fast and easy, vendor-specific certifications for just about any cloud service provider.

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Data centers have seen a lot of change in a short time. It used to be possible for organizations to run their service from a single data center and house their Domain Name Service (DNS) servers within it. It wasn’t an issue to have them in the same place, since if the data center went down, the DNS servers wouldn’t be of any use.
Of course, things aren’t so simple now. Organizations use multiple data centers, sometimes in multiple countries, not to mention cloud regions and highly distributed networks. Consequently, your DNS needs to be just as highly distributed as your content. After all, what good is a Disaster Recovery site if you have no way to direct your users to it?

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Cloud infrastructure, big data, and analytics are among the top technologies most likely to generate greater productivity, according to the latest report from Deloitte.

The findings, which appear in the firm’s latest report on mid-market technology, showed that more than a quarter of the 500 respondents argued integrating with existing apps and infrastructure was the key factor influencing how quickly cloud services were adopted.

41% of respondents admitted migration to the cloud was an issue of concern in terms of data privacy and security risks. Phishing (48%) was the most frequently cited answer, while 46% worry about risks that their employees introduce to the organisation.

The report also argued that finance and accounting is the most likely path to cloud success. 57% of respondents said there had been successful cloud deployments in these areas, followed by enterprise resource planning (33.6%) and customer relationship management (33%). 64% of respondents said they were actively building cloud solutions into their CRM, while 61% say they use analytics to increase the accuracy of forecasting.

“As these companies move further into the cloud, they are introducing tremendous value but also complexities that need to be understood,” said Karl Rupilius, principal and NetSuite practice leader at Deloitte Consulting. “Integration is becoming more important to manage, both in the cloud and on-premise as well.

“That’s the market’s next iteration: tying it all together and managing cloud integration more cohesively.”

The research findings are particularly interesting given they cover a more wide-ranging area of technology than the majority of cloud surveys.

“Other evidence of mid-market companies’ technology maturation includes their shifting focus around cloud-based services,” the report notes. “In last year’s survey, privacy and security risks were the leading factor deciding the pace of their cloud adoption. This year, such concerns took a big step back, and now the companies are mainly focused on issues around cloud integration.”

You can find out more about the report here.

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All too often, the restrictions of engineering seem to us like the laws of physics. Think back to when horse-drawn carriages were the best available mode of transportation. Drivers could only get to their destinations so quickly, given the needs of the horses, the wheels of the carriages themselves, and the quality of the roads. A trip from one city to another could take several days. At the time, that didn’t seem like an opportunity for revolutionary technology. It was just the way things were.

The same has been true for the way we power data across networks. We’ve been restricted by the physical capabilities of silicon, copper and fiber, as well as the heft of our data; but much like cars transformed transportation in the early 1900s, DevOps is allowing us to stretch the laws of physics.

Even though DevOps has been able to automate the delivery of the data behind applications and databases, it has been unable to hasten the transfer of that data. It’s as if DevOps is an engine that replaced a horse, but didn’t change the length of the journey or the quality of the roads.

So the question is: is this as good as DevOps can be? Is there something we could be doing to move our data even faster? Maybe there’s a better way to leverage our new engine to maximize efficiencies. Maybe we can eliminate the constraint of the roads themselves.

If instead of putting our DevOps engine into automobiles, we put that same engine into an airplane, all of the sudden we’re not dealing with the potholes and traffic jams of data bottlenecks.

This is the exciting challenge now posed to today’s technologists. We’ve moved data around in the same way for decades, constrained by Moore’s Law, without any regard for the enormous expansion of data each organisation is undergoing. But with this many packets of data trying to cross the same number of cables in the same way they always have, we’ve created a multiplying set of constraints, even within a process that is largely automated and therefore should be optimised.

However, the real result is far from optimal. We’re moving the same data over and over again within an organisation. And because it takes so long to move data, teams are using stale data rather than go through the process of requesting it. If they do request it, they often have to wait so long that the newly delivered data is already stale. If our goal is to make real-time decisions based on our real-time data, our current infrastructure falls painfully short.

We need to rethink the way that data is moving. Our current infrastructure is already swamped by today’s tidal wave of data, and every new user and new solution will only make things worse. In essence, to get the most out of our DevOps engine, we need automobiles to sprout wings.

We owe it to ourselves to emulate the Wright brothers, who simply asked if flight might be possible. Flight ispossible, and just as airplanes proved that there was more to transportation than cars in 1903, data virtualisation has proven that it’s possible to move more data, faster and cheaper than ever before.

The key to that flight is that most of the data flood consists of duplicates, and up to 90% of all non-production data an organisation uses is identical. Developers, testers, and analysts all need many copies of the same data, taking up immense amounts of storage and valuable time that could be used for more innovative endeavors. By retaining those copies in a central repository, versioning their incremental differences, and intelligently sharing only the requested data to end users – in a word, by virtualisation – we can reduce the flood and speed delivery. All we need is to replace ongoing maintenance and accumulation with insight and innovation.

Flight revolutionised transportation; and data virtualisation will revolutionise data management processes, allowing DevOps to power through the data deluge.  Now, it falls to each organisation to empower their IT groups with data virtualisation capabilities so that their DevOps practices can really soar.

The emerging Internet of Everything creates tremendous new opportunities for customer engagement and business model innovation. However, enterprises must overcome a number of critical challenges to bring these new solutions to market.
In his session at @ThingsExpo, Michael Martin, CTO/CIO at nfrastructure, outlined these key challenges and recommended approaches for overcoming them to achieve speed and agility in the design, development and implementation of Internet of Everything solutions within your organization.

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