AIOps – How AI Optimises Network Operations

As digital connectivity becomes increasing complex, network operations are becoming the unsung hero that ensures the seamless flow of information across the organisation – and often around the world. While conventional tools and methods may provide some information, they’re ill-equipped for this new landscape. This is where the transformative power of artificial intelligence (AI) comes into play, helping you to redefine your approach to operating and supporting your network. In this article, we’ll show you how this works in reality using the AI-native network platform from Juniper Networks.

The introduction of new technologies is usually surrounded by plenty of interest and hype. At the same time, revolutionary technologies divide time into “then” and “now”. We’re currently experiencing such a turning point from “then” to “NOW” due to the rapid development of artificial intelligence and its application in so many areas. An area where this is having a particularly strong impact is network technology. “Then”, before AI existed, was marked by slow, manual processes, IT teams overloaded with support tickets, loss of productivity due to network outages, missed business opportunities, long waiting times for downloads and endless teleconferencing issues.

Current challenges in network operation

Operating networks today requires constant vigilance. With the increasing complexity of networks, the maintenance, troubleshooting and optimisation of these digital ecosystems can sometimes overwhelm IT teams. It’s no longer simply a question of ensuring that everything runs smoothly, but that the paths along which the data moves enable an optimal flow – quickly, reliably and securely. Meeting this challenge requires more than conventional tools can offer.

Why AI? Insight into the reality of AI-supported network operation

Imagine the impact of new tools that are not just reactive, but proactive – or even predictive. Tools that not only alert you to anomalies, but also anticipate them and prevent them from ever negatively impacting the user experience. This is the promise of AI in network operations – AIOps for short.

Let’s look at a current example. Just imagine: you occasionally have latency problems in the network that affect a critical segment of your infrastructure. You ask the support team for help to find out what’s causing this. With traditional tools, this would require manual review of logs, hypothesis testing and perhaps the use of packet sniffers – all of which is likely to take days or even weeks, tying up a lot of labour and valuable resources.

Now imagine that support is driven by AI tools that have been developed over many years through continuous learning from thousands of networks. These tools not only determine the root cause almost in real time, but in many cases can also predict its probability and suggest preventive measures that may even resolve the problem without any human intervention. If that sounds like an impossible dream, it isn’t. It all actually exists.

AI-native network platform reduces operating costs and support overhead

The transformative potential of AI is undeniable and offers lucrative prospects – for network operations, for example. The integration of AI into the support process is more than an evolutionary step – it’s a quantum leap in the way it supports the management and optimisation of digital infrastructures.

Can you imagine a network that monitors, configures and repairs itself? AI models that have been developed and trained over many years using practical network data. A network with a conversational interface recognises and processes natural language in order to proactively maintain and optimise network performance, providing a consistently high-quality user experience, increasing the productivity of IT teams and saving costs. In more concrete terms, it’s a network that can be deployed around nine times faster, generates up to 90 percent fewer support tickets and 85 percent lower operating costs, and requires around 50 percent less time to resolve network incidents. These figures come from companies that use Juniper’s AI-native network. The future is “now” – the NOW way to network.

Juniper AIOps is a central element of Juniper’s AI-native network platform. It ingests data from multiple sources to provide in-depth user experience insights, including Juniper wireless access points, Ethernet switches, Session Smart™ routers, WAN edge routers and SRX firewalls. By combining deep data science algorithms, comprehensive domain knowledge and Marvis, the industry’s only AI-native virtual network assistant (VNA), Juniper AIOps reduces network incidents, support tickets and on-site appointments, all without human intervention.

This gives you greater control over all connections and also ensures an enhanced user experience. Whether you’re looking to deploy AI in your network or create the optimal network for AI utilisation, Juniper provides the agility, automation and assurance you need to simplify operations, increase productivity and ensure reliable performance.

Caption: with AI generated image