The number of problems that can occur in a network is countless. In a moment like that, who wouldn’t want a trusty fixer by their side to come and save the day, just like Mr. Wolf got Vincent and Jules out of a jam in ‘Pulp Fiction’? You can rest easy now – ExtremeCloud IQ CoPilot has your back!
Computer networks. What can go wrong, right? Well, if you’re an IT administrator, you probably have a good idea about how many things can potentially go south. High interference, sticky clients, problems with specific client or OS type, bad cabling, faulty ports, insufficient power, excessive amount of traffic exhausting hardware resources… The list can literally go on and on, and we have only so much time to introduce the fixes.
Some of the problems are chronic, others seem to appear completely out of the blue, almost making you wish you had Mr. Wolf’s number…
Network problems? Seek and… fix!
The very first step to solving any network issue is to identify and know the reasons for the particular problem. In most cases, once an anomalous network behavior is spotted and the root cause becomes known to us, resolving it tends to be a walk in the park.
Although ExtremeCloud IQ CoPilot has been designed to proactively prevent problems in the first place, it also seeks to drastically reduce the overall Mean-Time-To-Resolution. Here’s how it works, step by step:
- Mean-Time-To-Identify – the Events and Alarms capability allows each network to have custom alerts based on pre-defined sensitivity levels. ExtremeCloud IQ Companion is a mobile app that allows IT to get alerts about issues that happen in the network, even while they are on the go or away from the office.
- Mean-Time-To-Know – instead of searching a needle in a haystack, what if you got a simple view of how wired and wireless clients experience the network? What if you got an ability to look through the various anomalies in your network and the data that led to this conclusion? The following screenshot shows the Connectivity Experience for wired/wireless users, giving you the intuitive context and insights to help reduce the time you need to know what is happening to them.
- Mean-Time-To-Fix – explainable Machine Learning algorithms are a subset of the full spectrum of ML algorithms that allow you to understand why a recommended fix is suggested. For help with fixing issues, CoPilot provides videos and detailed knowledge base articles tied to each anomaly that are linked from within ExtremeCloud IQ. Finally, if IT operations teams are unable to remediate the issue themselves, then a GTAC case can be opened within the app itself with all the associated information, helping to simplify IT operation workflows.
But why worry about problems when you can prevent them in the first place?
Actively solving problems is one thing, but the lifecycle of some network issues can start long before the actual deployment, due to the lack of proper understanding of the used devices and their capabilities. To mitigate the risk before initial design and installation phase, many organizations invest in test labs to see how their devices will work in the field. However, such actions only add further strain on their already stretched budgets.
To address that challenge, we have recently added the Digital Twin capability to the ExtremeCloud IQ CoPilot solution.
ExtremeCloud IQ CoPilot: your digital twin for AIOps
More and more networking environments are becoming cloud-driven. The growth of advanced cloud capabilities allows us to process data in a whole new way, even enabling us to create digital models of actual network devices.
How does it work?
Run ExtremeCloud IQ CoPilot. Select your operating system, along with an optional policy that you may want to apply, hit ‘Launch’ and… voilà! You can now play with a digital model of your favorite Extreme Networks Universal Switch without getting off your sofa or paying for expensive test lab space by simply observing its user interface within ExtremeCloud IQ or opening a command-line-interface. Want to familiarize yourself with the platform, OS version and configuration before having the physical switch in-hand? Wondering what would a modeled network look like? You can find answers to these questions right here!