Frustrated with the impact of technology advances on infrastructure upgrades and IT budgets, a growing number of organizations are opting for cloud computing investments instead.

That is the view of Bluelock Chief Technology Officer Pat O’Day, who shared his predictions for cloud computing and machine learning with Information Management. O’Day sees four key trends driving cloud computing in 2017.

More companies will turn to the cloud than new hardware 

“There’s a lot of churn in the hardware space because of virtualization,” O’Day explains. “Companies are growing tired of having to refresh their IT systems with new hardware every five years. People want to be more mobile, and the cloud is a way to get there. Plus, rapid technology innovation has driven increased competition (think about the rise in artificial intelligence, for example).”

“For these reasons, more and more businesses are opting for a model that allows them to harness immediate time-to-value and consistently have the latest technology. With the cloud, now even the smallest companies can compete on the technology front,” O’Day says.

Cloud vendors with incomplete solutions will form surprising alliances

“Companies that lack solutions in the cloud industry will be left behind in the crowded landscape of competition,” O’Day predicts. “Therefore, we’ll continue to see the formation of surprising alliances to mitigate weaknesses. Would you have ever pictured cats and dogs living together? Get ready. An example of this consolidation is the VMware and AWS partnership to diminish gaps in their public and private cloud offerings.”

SaaS will emerge to help people manage cloud-based resiliency 

“There’s a growing science around resiliency, not just because of technology improvements, but because there’s an inherent link to the efficiency of people and process,” O’Day explains. “Data protection is now a table stakes investment. People increasingly want to perform tasks and receive services through software, with the streamlined convenience of enterprise platforms, such as Salesforce and ServiceNow. Contrast this with the time-consuming inconvenience of having to perform DR tasks manually, and you’ll find that it’s no surprise this efficiency-focused approach to the DR process has become popular.”

Machine learning will help predict application downtime and duration 

“The Internet of Things and big data have driven huge developments for higher living standards, and machine learning has emerged as part of this goal. In 2017, we’ll see an increased use of business intelligence to make predictions,” O’Day says. “A good example of this approach will be machine learning to predict recoverability, which will continue to grow more granular as users will set policies and make decisions for wider business initiatives based upon this real-time information. Basically, you shouldn’t be using a cloud that doesn’t use machine learning at this point.”

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