Potent SDN and Big data synergy

To reap the full benefits of Software Defined Networking, SDN applications must dynamically respond to the environment in which they live

Tags: A10 Networks Inc (www.a10networks.com )Software Defined Network
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Potent SDN and Big data synergy Glen Ogden, Regional Sales Director, Middle East at A10 Networks.
By  Glen Ogden Published  February 28, 2016

SDN is fundamentally about programmability, the separation of forwarding from control, and the ability to dynamically configure service and network elements in real time. However, to reap the full benefits of Software Defined Networking, SDN applications must dynamically respond to the environment in which they live. Big data offers the ability to characterize that environment, in terms of state, behaviour, anomalies, and long-term trends.

While big data offers the promise of new and potentially surprising forms of insight, you don’t get this ‘for free’ by simply deploying Hadoop. You need to apply machine learning or statistical analysis techniques and non-trivial data science, based on the application context. As analysis and visualization tools mature, the value of this insight will take an increasingly important role in both the design and long term operational aspects of converged data centres, and in the design and running of services offered to users.

In the context of SDN, this convergence with big data offers a particularly interesting dimension - a feedback loop - the ability to take analytics and state change events and dynamically inject those back into SDN decision-making, guided by a policy engine. This promises to make next generation data centres highly tunable, highly automated and responsive to real-time changes in operational use and behavioural trends.

Imagine the capability to setup, teardown, and scale-out ‘service-chains’ for individual workflows dynamically, by time of day, geo-location, traffic demand, and security context; all under fine-grained policies and with different SLAs. Over time, this insight could be essential in maximizing top line, improving customer retention, raising brand awareness, and maintaining competitive edge. Although the gains from these insights are relatively modest, in today’s highly competitive market, it could be the difference between a market leader and an ‘also-ran’.

This is only the ‘end of the beginning’

Bringing all of the potential from big data to SDN is not trivial. Although this field is evolving rapidly, there is still a way to go before we see complete and widely published reference architectures in place.

Right now we are probably closer to the ‘end of the beginning’ for machine learning and analytics on big data, and the ability to inform SDN decision-making consistently and accurately, based on policy and dynamic feedback.

Early adopters and more foreword-thinking organisations are already gaining experience in the trenches, but many of the tools, interfaces and standards are still evolving.

Furthermore, the closely related technologies such as virtualisation, cloud, service-chaining, NFV, etc. are all in a state of flux.

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