There’s a treasure trove of invaluable data that can help companies run their businesses better. And it’s sitting right in front of them, running over their own corporate networks. But getting to this data and making sense of it all has become a monumental challenge for enterprises looking to improve the productivity of users.
Managing and monitoring networks has always been essential to IT operations. While vendors deliver discrete tools that let network managers troubleshoot their products, the market has evolved to the point where this model is no longer tenable. The amount of data coming from so many different sources has forced network managers to become data scientists — analyzing and correlating device logs, packets and Wi-Fi metrics to figure out where problems are hiding and who is being affected, when and where.
In the Beginning…
Before mobility, virtualization and cloud apps, fixing network problems was relatively easy as users simply plugged into Ethernet jacks to access local applications and resources. When a user had a problem, they would call the help desk and someone would try and recreate the problem or go check a handful of monitoring tools that might give them a clue into what’s wrong. That model of network operations no longer works.
To be effective in today’s mobile enterprise, networking staff need to get in front of problems before they happen. If they don’t, they are simply relegated to network firefighting.
With the increased complexity of enterprise access networks, the proliferation of different devices with different operating systems and the use of applications and services — often not under IT’s control — getting to the heart of individual user and systemic client network problems has become the new network nightmare. Just think about what happens when a single user connects to the network.
First, they must access Wi-Fi using one of their smart devices. Next, the user must authenticate to the network, obtain an IP address and resolve DHCP requests. Finally, they access applications locally or in the cloud over a wide area network link. A problem with any of these transactions can result in poor user experience, which the users blame on “the network.”
But was it a device OS problem? A Wi-Fi issue? An application failure? A WAN problem?
Pinpointing the root cause of user network incidents has become a daunting task. Network managers must use a multitude of vendor tools, gather their data, analyze the data and correlate all the results across every layer of the network.
This is a particularly acute problem within the local access network. Highly mobile users armed with a myriad of smart devices accessing cloud-based applications make difficult for IT staff to get a good grip on the user network experience. Analyzing real-time and historical trends to improve client performance, network reliability or proactively plan for additional users and network-sensitive applications simply aren’t practical. The use of big data network analytics is widely believed to be the next big step in solving some of these pressing infrastructure management challenges that conventional tools were simply never designed to tackle.
This industry-wide problem demands a new class of network infrastructure solutions that capture the treasure trove of data traversing the network to deliver deep insights and a holistic view of the network, devices, services and applications from the perspective of the user.
A new class of network infrastructure management that examines the users’ abilities to perform and be productive on the job can revolutionize traditional infrastructure management and give companies broader and more holistic insight into how the network stack is behaving throughout the entire user experience. These new user performance management platforms fundamentally alter the traditional reactive workflows of IT staff and network managers.
Using a combination of big data analytics technology, cloud-computing and machine learning techniques, a user performance management platform can automate the learning process and get to the heart of user network problems that negatively affect performance, no matter where they are hiding.
By constantly observing the network packets, a UPM platform watches and learns the behavior of client transactions up and down the stack as they happen, storing this data historically to identify larger patterns and trends that are emerging.
The result is improved user performance and productivity, optimized network operations, faster service desk remediation, and improved capacity planning and ability to quantify IT investments.
Netflix for Networks
One of the biggest benefits for approaching infrastructure management from a user performance view is the ability to get a recommended list of precise configuration actions that network managers can take to fix specific client incidents or systemic infrastructure problems that impact user performance across the entire infrastructure.
Recent advances in big data analytics, when combined with cloud computing and machine learning make it possible for network managers to be more proactive.
Just think about how Netflix works. When you watch a movie or TV show, Netflix is learning what might interest you based on historical viewing data it keeps. It then suggests potential shows that you might like to watch without you even asking.
Now apply this concept to the enterprise access network.
Using this construct, user performance management tools collect wired packets, device data, wireless metrics, applications and WAN data. These systems then correlate and analyze all this data concurrently to understand important patterns and trends that impact user network performance from virtually any dimension.
For instance, to fix a Wi-Fi performance problem causing user connectivity issues in a certain location, remediation recommendations, depending on the specific problem, could include changing channel assignments on certain access points, boosting transmit power, or turning off radios causing interference.
User performance management systems crunch massive volumes of data and correlate this it across different dimensions to understand what’s happening in the network. In turn, remediation recommendations can be automated and surfaced, often, before network staff realizes there is a problem.
And because this is being approached from the user perspective, managers know how big a problem each incident is and, if fixed, how big the benefit — something IT leadership is dying for.
Every time we log on to Netflix we’re adding to the data pool that helps deliver a good user experience. The enterprise network is full of data that can be used to help deliver a better user experience, but traditional infrastructure management tools fall short in their ability to capture all of it and make sense of it. Big Data network analytics, artificial intelligence and machine learning combined with the power of cloud computing now pave the way to a new approach to infrastructure management that moves away from the old days and adopts new ways of harnessing that data to give network managers their lives back and keep users wildly happy.
Feature image via Pixabay.