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Juniper: Machine Learning Isn’t All We Need for Smart Networks

Submitted by on April 15, 2018 – 6:05 amNo Comment

Software-defined networks give you flexibility, but to make them really effective at scale we need to take humans out of the loop and use automation to respond more quickly  – like taking an optical link down for maintenance and moving the traffic over to another line automatically as the latency rises. Plus, we need to do that before the speed drops enough to cause problems for the workloads relying on that connection.

 

 

That kind of automation will create something more like a “self-driving” network, Juniper platform systems CTO Kireeti Kompella told Data Center Knowledge; but just as with self-driving cars, the prospect is exciting but also raises some long term concerns. This is about creating adaptive, self-customizing services built on the flexibility of SDNs and Network Function Virtualization which means that instead of being a monolithic device, network hardware exposes APIs and functions. But even though we have what Kompella calls “power sharing between equipment makers and the people who deploy networks, who want more of a say in how systems are being built,” the problem is that it can also end up like parents fighting, forgetting about the children caught in the middle.

To read the entire article, please click on this http://www.datacenterknowledge.com/networks/juniper-machine-learning-isnt-all-we-need-smart-networks