Can AI get you from network monitoring to proactive observability?
How do we move from network observability to proactive monitoring? It has been a challenge for most network teams for decades. One of the problems network teams face is the vast volume of data they deal with and the lack of time and skills to interpret it.
Two decades ago, that data was generally contained, with the majority of traffic understood by network teams. Today, the explosion of cloud apps and remote working has made understanding traffic a significant challenge. It is not just the volume of data but the complexity of that data that makes the challenge hard to overcome.
So, where do we start? To find out, Enterprise Times talked with Stephen Amstutz, who’s the head of strategy and innovation at Xalient. Amstutz believes that the move to software-defined networking gives us a chance for greater observability of data. He talks about the gains from having greater granularity into how applications are consuming the bandwidth.
But this is not just about utilisation. Amstutz says, “Not only are we getting utilisation statistics, but we’re also getting all of the metadata that goes along with that, so we know what applications are being used and consumed, and we know what users are consuming those applications. We’re able to much more effectively understand how the network is being used.”
That understanding allows an organisation to set its Quality of Service metrics to prioritise key applications. It also highlights where legacy applications are still in use. A critical area when companies are moving to the cloud.
To hear more of what Amstutz has to say, listen to the podcast here: Can AI get you from network monitoring to proactive observability? – (enterprisetimes.co.uk)