Artificial intelligence (AI) technologies like machine learning, virtual assistants, and process automation are driving revolutionary capabilities across the enterprise. Yet, arguably the greatest area of untapped opportunity is with AI and IT operations (a.k.a. AIOps).
AIOps applies AI and analytics to network visibility and management capabilities. AI in the network helps IT teams better understand what’s going on, optimize bandwidth efficiency, and act in response to changes in network behavior, context, and load. Essentially, these technologies can act as a virtual network engineer, multiplying your workforce with a 24 hour assistant. Moreover, AIOps serves as the foundation for creating a fully autonomous network. Much like self-driving vehicles, the tools we need to create an autonomous network are available today–it’s only a matter of putting them into practice and perfecting them.
The benefits of AIOps are enormous. According to Gartner, “organizations that automate 70+% of their network change activities will reduce outages by at least 50% and deliver services 50% faster.”
For two reasons, today’s IT teams aren’t fit for comprehensive network analysis. First, under the pressures of trying to do more with less, IT teams aren’t growing as the pace of technological change accelerates. In a new study from Dynatrace, 76% of CIOs agreed it could become impossible to manage digital performance as IT complexity increases. Eighty one percent believe AI will be critical as a result, with 83% either already or planning to deploy AI in the next 12 months. AIOps is needed for IT to operate at the speed of today’s digitally driven, constantly changing business needs.
Second, machine learning and behavioral analysis are simply better at the job. AIOps virtual assistants are designed to help IT teams build a full, comprehensive view of network activity. They deeply understand what constitutes “normal” activity, for example, and can sift out potential performance- or security-affecting events. Furthermore, they go beyond identifying “normal” network behavior to maintain a dynamic picture of what constitutes this behavior as the network changes over time.
Specifically, AIOps virtual assistants provide:
As a result, teams gain a more thorough grasp of their IT environment, empowering them to design and maintain the playbooks AIOps tools need to start reacting to performance problems and service failures. Ultimately, this allows IT to spend less time on administrative management and more time on strategic work.
Just as virtual assistants support contact center agents in automating post-call work and advising on which step to take next in the call flow, network virtual assistants provide expert guidance on design and problem solving, helping IT teams automate mundane management tasks. Specifically, AIOps virtual assistants provide recommendations to optimize multi-cloud environments:
Learning from IT team feedback and using automation tools, AIOps can then be coached and trained to solve problems and modify the network for future situations as needed. Learn more in the guide to AIOps by Nemertes Research.
Network readiness is a large factor in AIOps success, as these tools must have the raw data, network visibility, and computing power they need to evaluate the IT environment. And in order to act, they need access to network bandwidth controls and configuration consoles. Here’s a checklist of things you’ll need for success:
Now that you have a list of the necessary requirements, here’s an infographic with the four steps needed to pave the way for autonomous networking with AIOps.
Ready for a deep dive into AIOps? Don’t miss this guide written by analysts at Nemertes Research:
Are We There Yet? Autonomous Networking and the Rise of AIOps
Paving the way for virtual engineers, augmented operations, and automation on a self-managing network
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