Putting analytics to work for virtualized networks

Just as the human autonomic nervous system changes heart rate, blood vessel size and blood pressure without user intervention, networks will soon evolve into autonomy.

This ideal has hardly been realized to date, partly due to the untapped potential of Big Data analytics. If you're trying to improve your IT framework, you likely know that harnessing big data is part of the future of the enterprise. But what does machine learning have to do with virtualization?

A lot, it turns out. Big data will help companies realize truly optimal yields from investments in critical infrastructure because, by definition, the associated machine learning allows systems to adapt to variable requirements without being explicitly programmed to do so.

Michael Vizard of SDx Central writes that companies like VMware are already acquiring analytics software to bolster their capabilities.

"Clearly, the implications of being able to holistically correlate data drawn for all the layers of a distributed computing environment are profound," Vizard said. "Not only will companies be able to better optimize the flow of data moving across the network, but in many instances they will have visibility into how any given business process is being consumed."

Big data can influence a wide range of areas within IT, especially the network virtualization space.

While SDN alone foretells the future of adaptive networking, it is Big Data that will ultimately unlock the potential of automated network operations. Contact CloudSmartz to leverage the practitioners who have achieved the future.

At CloudSmartz, we see various Big Data use cases that service providers could benefit from fact-based,

analytics-driven decision making.

Contact CloudSmartz to learn more about the proper way to transition to a future network.