Auvik Leverages Agentic AI to Address Growing Network Management Challenges
The increasing complexity of modern IT networks, coupled with a shortage of skilled professionals, is creating significant challenges for organizations managing multi-vendor environments. IT teams are grappling with an ever-increasing volume of alerts, often lacking the expertise to efficiently address them. Agentic AI is emerging as a potential solution, and Auvik, a cloud-based IT and network management platform provider, is the latest vendor to embrace this technology. The company recently launched Aurora, an agentic AI platform designed to move beyond simple alerting and into automated remediation, aiming to streamline network operations and alleviate the burden on IT staff. This move reflects a broader industry trend toward leveraging artificial intelligence to address the growing skills gap in network management.
For 15 years, Auvik has focused on providing network management solutions accessible to organizations that may not have the resources for complex, on-premises tooling, supporting diverse vendor ecosystems. The development of Aurora was directly influenced by customer feedback, which emphasized the need for AI solutions that deliver tangible results, not just theoretical capabilities. “Our customers have been extremely clear, and our customer advisory boards, when you reach out with something, it has to be something that solves real world problems, and not just AI or agentic, for the sake of AI,” Doug Murray, CEO of Auvik, told Network World. “We expect you to provide us with an experience that is going to help me automate and simplify things. That’s what we care about. We don’t care about some fancy AI nomenclature.”
How Aurora Simplifies Network Operations
Traditionally, Auvik’s platform alerted IT teams to network issues. Aurora builds on this foundation by not only identifying problems but also providing specific guidance on how to resolve them, with the long-term goal of automating remediation tasks. This shift is designed to empower IT professionals, even those without specialized networking expertise, to effectively manage their infrastructure. The platform’s new capabilities include several key features designed to improve efficiency and reduce response times.
- Alert Prioritization: Aurora ranks incoming alerts based on their potential impact, using a red/yellow/green system. This allows technicians to quickly identify and address the most critical issues, reducing alert fatigue and improving focus.
- Device Lifecycle Management: The platform proactively identifies end-of-life (EOL) and end-of-support (EOS) devices, providing a ranked dashboard that highlights potential vulnerabilities and the scope of exposure. For example, it can pinpoint specific SonicWall Gen 7 firewalls requiring updates.
- CVE Monitoring (Beta): Aurora scans managed devices for known vulnerabilities, proactively surfacing potential security risks before they can be exploited.
- Scripting Assistance: For technicians unfamiliar with a device’s command-line interface (CLI), Aurora can generate scripts to automate remediation tasks based on natural language requests.
Auvik envisions Aurora as the “Do” phase of a three-stage framework – See, Inform, Do – that guides its product development. “See” represents visibility into the network infrastructure, “Tell” focuses on alerting and providing prescriptive notifications, and “Do” embodies the automated remediation capabilities of Aurora. Murray described the ultimate goal as achieving a level of automation that some might call “self-driving” network management, but emphasized that the focus remains on empowering users and simplifying complex tasks.
The Technology Behind Aurora
What distinguishes Aurora from other AI-powered network management solutions is its foundation in live network data. Auvik’s platform continuously collects data from managed devices, including state, topology, configuration, and performance metrics, creating a real-time view of the network environment. This data is then used to inform Aurora’s recommendations, ensuring they are tailored to the specific context of each customer’s network. According to Auvik, this approach is more effective than relying on generic training data.
- The Collector: Auvik’s on-network collector agent continuously gathers data from every managed device and transmits it to a central cloud repository.
- The Data Foundation: Over 15 years of operation, Auvik has amassed a substantial dataset, including over 300 million device configuration backups and 2.2 billion CLI command executions across hundreds of supported vendors. The platform currently manages more than 10 million devices daily.
- The Agentic Layer: Aurora’s architecture is described as “contextual,” meaning the AI agents operate based on the live data stream and historical patterns specific to each customer’s network. This requires significant data preparation and cleaning, a process that Auvik began four years ago.
- The AI Stack: The platform utilizes Claude as its primary large language model (LLM), with OpenAI models employed for specific functions. Murray noted that the adoption of agentic AI tooling over the past two years has simplified the process of leveraging Auvik’s historical data compared to previous machine learning approaches.
Addressing the IT Skills Gap
The development of Aurora is rooted in a fundamental challenge facing the IT industry: a growing shortage of skilled networking professionals. Murray highlighted the declining number of university graduates specializing in areas like Cisco CLI and deep networking expertise. This demographic shift means that a significant portion of the existing IT workforce with these skills is nearing retirement, creating a potential crisis in network management capabilities.
Aurora’s scripting assistance and push toward automated remediation are direct responses to this talent gap. By simplifying complex tasks and reducing the need for specialized expertise, Auvik aims to empower a broader range of IT professionals to effectively manage network infrastructure. “Being able to create this in a way where we try to make it such that you don’t need to be a networking person to run the networking infrastructure is really the vision of where we’re trying to take this,” Murray said. “So the more we can automate and simplify and help people with auto remediation, the more powerful the platform becomes.”
The increasing reliance on automation and AI in network management is not merely a technological trend; it’s a strategic response to a looming workforce challenge. As the demand for network services continues to grow, and the pool of qualified professionals shrinks, solutions like Aurora will likely become increasingly critical for organizations seeking to maintain reliable and secure network operations. The future of network management may well depend on the ability to effectively leverage artificial intelligence to bridge the skills gap and empower the next generation of IT professionals.
Auvik has not yet announced specific pricing details for Aurora, but further information will be released as the platform becomes generally available. The company plans to continue expanding Aurora’s capabilities, with a focus on further automating remediation tasks and providing even more proactive insights into network health and security.
Key Takeaways:
- Auvik’s Aurora platform utilizes agentic AI to automate network remediation tasks.
- The platform prioritizes alerts, manages device lifecycles, monitors for vulnerabilities, and assists with scripting.
- Aurora is built on a foundation of 15 years of network management data collected from over 10 million devices.
- The development of Aurora is driven by the growing shortage of skilled networking professionals.
The launch of Aurora represents a significant step forward in the evolution of network management, offering a glimpse into a future where AI plays a central role in ensuring network reliability, security, and efficiency. Retain an eye on Auvik’s website for updates on Aurora’s availability and features. We encourage readers to share their thoughts and experiences with AI-powered network management solutions in the comments below.