The importance of Machine Learning to assure virtual networks – Part II

In Part I of this article, we discussed how an effective service assurance solution can assure operators that their virtual networks will offer the same quality and performance as those of traditional WAN networks.

But as new technological advancements are made, we ask ourselves what role Machine Learning plays in an effective network performance strategy? In Part II we will cover the importance of Machine Learning when assuring your hybrid-virtual network environment.

Among the many advantages of virtualised networks is the ability to automate the remediation of network issues and optimise performance without manual intervention. While network monitoring has always been a reactive and manual process, the promise of SDN and NFV enables us to leverage advancements of AI and Machine Learning to enter a level of proactive monitoring that allows for evolution with virtual networks—unlike anything we have seen before.

Machine learning offers a level of intelligence that evolves with the network. By integrating this level of intelligence, those responsible for network uptime and performance can leverage assurance tools with Machine Learning functionality to automate many performance optimisation and service remediation use-cases.

Here are some of the advantages of today’s AI-aware service assurance solutions:

• Predictive analytics in a dynamic environment – Probably the most significant immediate benefit of these new intelligent networks is their ability to identify problems well in advance to avoid them. These problems can be costly, affect SLAs, and slow impact an operators’ business plans. Such predictive analytics are a critical investment for carriers looking for differentiation.
• Forecasted operational savings – As network intelligence improves, Machine Learning will allow for a dynamic understanding of performance. That means that an assurance tool can identify service performance problems well in advance of a customer impact that might result in SLA breaches and customer credits. This cost savings can be allocated to other parts of the business as a result.
• Avoidance of disruption – Customers will not experience the effects of a network disruption because the failure can be identified, correlated and automatically remediated before the customer notices the problem.
• Continuous customer experience during digital transformation – As the companies migrate towards virtualised and much more dynamic service environments, customers will experience more stable and adaptable services and enjoy a higher level of satisfaction.

The author of this blog is Anand Gonuguntla, CEO, Centina

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