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ML and AI enabled IT Ops: the NOC as a modern cockpit

ML and AI enabled IT Ops: the NOC as a modern cockpit

By |2019-05-17T17:32:19+00:00April 16th, 2019|Blog|

A common sentiment among our prospects after they see our demo for the first time is: “That’s it? It can’t be that simple!”.  

The truth is – yes it can be, and it should be.

ML and AI should make IT Ops simpler, and a big part of that is usability. If your ML & AI powered IT Ops tools take months to set up and weeks to learn, and then don’t provide a substantially improved user experience, you’re obviously using the wrong tools.

Less is More

Not too many years ago, in my glorious, full-head-of-hair, Ray-Ban-wearing youthful days – I was a pilot, and I can’t help but compare the process modern flight went through back then,  to the one that IT Operations is going through today with ML & AI.

Do you remember the Concorde, the supersonic passenger airliner that flew 100 passengers across the world at twice the speed of sound? Back then, It took three very able pilots to handle its crazily complex cockpit:

Photo Source:: Wikimedia Commons

Today, airliners like the Airbus 380 can fly up to 850 passengers, with only 2 pilots, operating a much simpler cockpit:

Photo Source: Wikimedia Commons

The change is not just a technology-enabled convenience – it is actually a necessity in modern flight.

Humans can no longer physically process and properly react to the gigabytes of information thrown at them by today’s complex flying machines. It takes a significant amount of computing power to process and control a commercial airliner’s many, many systems – while providing human pilots with just the right amount of data and information they need to safely fly it to its destination. The Concord’s gazillion gauges and dials are a thing of the past not just because technology allows it, but also because it necessitates it.

NOCs are very similar to cockpits:  they are central command posts that utilize “gauges and dials” which allow the operators to “fly” their businesses. And as enterprises develop and the digital transformation moves forward,  these operators need to support an ever growing number of complex services and apps, which legacy IT incident management solutions simply weren’t built for.

Overwhelmed with data and IT noise, they need smarter and simpler tools that will allow them to cope with this new world. Basically, they need AI and ML enabled IT Ops solutions.

Embracing the Change

These ML and AI enabled IT Ops tools are often eyed with suspicion and skepticism, because unsuccessful products and projects in the past have created lack of trust.

Oddly enough, the transition in the aviation world which I discussed above, suffered from similar problems. In their early days, “fly-by-wire” aircraft (the name given to computer-assisted-flight, when it was new) were met with apprehension, centering on the burning question of whether it was really wise to relinquish ultimate control of a plane to computers.

I distinctly remember the heated debates…The official launch of the Airbus A320, the first ever public demonstration of a civilian fly-by-wire aircraft, ended up with the plane crashing, and the pilots blaming the computers… But as the years passed, fly-by-wire matured and proved to be not only safe, but also a necessity. It was the only way to take aviation to the next level. To make planes fly faster, safer, cheaper, and allow them to provide comfort and cost-effective travel for almost everyone to almost everywhere. Today, no one can imagine any other form of flight, and even when malfunctions lead to accidents, it is clear that computer assisted flight is a fact of life, so lessons are learned and systems are improved.

The good news is that ML and AI in IT Ops have also matured, and a growing number of enterprises are in different stages of testing and implementing such solutions.  

BigPanda Autonomous Operations is itself being used by global leaders such as Cisco, Turner, Workday, United Airlines and many, many more. They have all learned to trust and rely on our Open Box Machine learning, that gives them full transparency, testability and control. And when our CS or PM teams visit their NOCs, more often than not, they find a single, simple screen in the middle of it all – just like in all modern cockpits.

And that screen is BigPanda.

About the Author:

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Yoram is the Content Manager at BigPanda, where he leverages his extensive experience in R&D, Marketing and Bizdev at both large enterprises and startups to tell stories through written, digital and video content