About The Speaker
Surviving IT: My career has been peppered with long roles, and short contracts. I’ve always enjoyed IT because, save for support roles, I typically don’t have contact with people outside the organization, which is something I was deathly afraid of. In 2019, I started a new job at a great company full of wonderful people. Two weeks later, my wife left me. Having spent nearly 20 years in IT (and a hell of a lot more than that working with computers at home), it struck me that maybe continuing to do what I’ve been most comfortable doing isn’t actually what I should be doing. So when Josh Manley came and asked me to be the sole technical sales engineer at Nagios, to be on the phone and interacting specifically with people who are not part of the company, I said, “Sure.”
Transforming Nagios with AI: Building an LLM-Powered Monitoring Assistant and Predictive Anomaly Detection Engine
We at the Ellucian monitoring team are drowning in alerts, logs, and complex distributed systems, which is making it harder than ever to identify root causes quickly. In this presentation, we showcase how we integrated Large Language Models (LLMs) and AI-driven anomaly detection with our enterprise Ellucian Nagios to radically improve incident detection, triage, and response. We demonstrate how an LLM-powered Monitoring Assistant can interpret Nagios alerts, summarize system health, and provide context-rich remediation suggestions. The assistant converts noisy alerts into clear narratives, analyzes logs in real time, and offers guided troubleshooting steps through ChatOps interfaces, dramatically reducing cognitive load for the monitoring engineers. Alongside this, we introduce our AI-enhanced anomaly detection layer that analyzes time-series and historical performance data to identify subtle deviations before traditional thresholds are crossed. By predicting likely failures and prioritizing alerts based on impact, AI elevates Nagios from a reactive tool to a proactive observability partner. We will share actionable architecture patterns, prompt-engineering techniques, failure-safety considerations, and integration strategies using APIs, plugins, and automation frameworks. Attendees will walk away with a blueprint for augmenting Nagios with state-of-the-art AI capabilities—without replacing their existing monitoring ecosystem. This talk is ideal for organizations seeking to modernize their monitoring workflows using AI.
Behind the Session Title
Lessons Learned, Lessons Applied: Stories from my past, and how I’ve applied them later in life, often during technical demos. Turns out, working as a jack-of-all-trades kind of role in IT will let you speak somewhat intelligently to a wide range of audiences. Some stories are about taking what I know, and expanding on that knowledge on the fly, during a demo. Some are just stories I like to share because I’d like to see change in how IT is handled.
What I Hope You Learn
Why Attend: Come to hear stories about personal growth and building trust on calls with prospective clients, stay for the dad jokes and hot takes about IT.
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