Cisco’s Intent-Based Networking

Tuesday, June 20, 2017 @ 06:06 PM gHale


Cisco has a goal to introduce “intent-based” networking that can deliver security and networking that learns, adapts, and gets smarter over time through the use of artificial intelligence.

Intent-based systems operate in a manner where the administrators tell the network what it wants done and the “how” is determined by the network and then the specific tasks end up automated to make this happen, Cisco said at a media event Tuesday in San Francisco. One case in point could be if a business wants to secure all traffic from marketing, that command ends up issued and the systems would take care of all the technical details.

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The analogy of an autonomous car has been used to illustrate a traditional network versus an intent-based system, officials said. A traditional network is a bit like a self-driving car where many tasks, like lane changes and turns can be automated. An autonomous car is continuously gathering information and can adapt as the conditions change. If traffic gets congested, perhaps the car takes an alternate route. The data gathered by the car creates a closed-loop system to make the car smarter and more predictive.

Cisco’s new solutions want to allow businesses to deploy a network that can scale from thousands to millions of connected devices while leveraging a closed loop system to constantly learn, adapt and automate network operations to better secure the environment and optimize application performance.

Cisco’s intent-based networking employs contextual information and then ends up acted upon by machine learning based “intuition.” The pervasiveness of Cisco infrastructure allows it to collect network traffic but also contextual information such as who users are, what resources they are accessing, where they may be located and how endpoints are connected. This information can end up used to create customized experiences and improve security. Machine learning is used to analyze what the contextual information means, gather new insights and then predict outcomes. This is critical in being able to turn data into actionable insights.



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