At a network operations center (NOC), getting a flood of helpdesk requests full of complaints from users at every corner of a large distributed network is a sure way to ruin everybody’s day. For IT staff, the goal isn’t just to keep the network up and running, it’s to keep it running well. Slowdowns, wireless problems, DHCP issues, DNS issues, VLAN configurations, and security and password issues all keep users from getting their work done. And then nobody is happy.
As networks grow, they tend to get more complicated. And the more complex a network becomes, the more likely it is to have problems. Today, many organizations have hybrid networks that span both on- and off-premises environments in addition to SD-WAN with 5G/LTE wireless WAN gateways that can have capacity constraints.
Trying to manage and troubleshoot today’s sprawling distributed networks has stretched many IT teams to the breaking point. Even worse, the technologies and solutions IT staff have typically used to track network availability, performance, and trends often can’t keep up anymore. On a large network, because there are so many solutions generating so much information, sorting through it all can be difficult or even impossible.
AI to the Rescue
To deal with the ever-increasing amounts of data, more solutions are taking advantage of artificial intelligence (AI) and machine learning (ML) to streamline and accelerate the detection and response to networking challenges, ideally before they affect the network and users. Today’s AI-based management tools for IT operations (AIOps) are designed to maximize network visibility, improve response times to anomalies, and reduce ticket volume by proactively remediating network issues.
Putting AI to work is a great start, but many AIOps solutions don’t include security in the equation. Networking and security need to be converged across the LAN, wireless LAN, SD-WAN, and WAN gateways using a platform that takes advantage of AIOps. By combining a cybersecurity mesh architecture with AIOps, organizations can achieve a level of automated detection and response that simply isn’t feasible when networking and security are siloed. Converging networking and security with a cybersecurity mesh platform improves network visibility, which reduces response times to anomalies and makes it possible to proactively remediate network issues. Using AI and ML-driven predictive modeling, IT teams can actually solve problems before they happen.
Instead of having multiple individual views into small segments of the network, by converging networking and security means IT teams have a common view of what is happening across the LAN, wireless LAN, and all WAN aspects. Everything can be monitored using a single operating system and management console, which can provide insights IT staff can use to proactively optimize the network.
Key AIOps Capabilities
Not all AIOps solutions are created equal, so organizations should make sure that the solution the choose includes these capabilities:
- Visibility into the entire network. The AIOps solution should cover everything, including local-area network(LAN) elements, wide-area network (WAN) [including both logical entities such as SD-WAN and physical entities like WAN gateways], and security. Avoid solutions that cover only one or two areas or that only specialize in a single technology.
- Good performance with low overhead. The data coming into AIOps can increase network overhead, so it’s important to select a solution that doesn’t cause a major performance impact.
- Insights into trends. AIOps solutions should include trend analysis with insights into changes in use patterns to predict potential issues.
- Simplified operations and integration. To gain value from AIOps, IT staff need good feedback and actionable intelligences with a single view into the network.
Transforming IT Operations
Adding AI technology into network operations has the potential to transform IT operations. When AIOps is integrated across networking and security, it not only can identify problems, it can offer recommended resolutions as well. Based on trained ML models and detect probable root causes, it reviews configurations to help predict failures before they happen. Combining a converged network and security platform with AIOps provides insights that give IT staff the information they need to make improvements that span the entire network.
Find out how FortiAIOps uses AI and ML to improve visibility and IT operations across distributed networks.
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