Kentik networking experts Chris O’Brien and Nina Bargisen join Capacity Media’s Jack Allen to explore the evolving role of AI in network monitoring. They delve into historical applications of AI and machine learning in network observability, the integration of large language models for enhanced troubleshooting, and the significance of diverse network telemetry data sources.
The session includes a live demonstration of the AI-assisted query features of Kentik NMS (Network Monitoring System) and highlightings the advantages of streaming telemetry over SNMP. There’s also an insightful Q&A session at the end. This webinar replay is a must-watch for anyone interested in the intersection of AI technology and network management.
Learn more about Kentik NMS, the next-generation network monitoring system here.
Key takeaways from this webinar include:
- AI and machine learning have been explored in network observability for over 15 years, aiming to enhance monitoring efficiency and accuracy.
- Large Language Models (LLMs) like ChatGPT offer new possibilities for troubleshooting and interacting with network data through natural language processing.
- Streaming telemetry is highlighted for its efficiency and granularity in data collection, compared to traditional SNMP methods.
- Kentik’s NMS and Query Assistant AI features demonstrate practical applications of AI in network management, emphasizing real-time data analysis and comprehensive network visibility.
- Challenges in applying AI to network observability include ensuring data accuracy, model training, and integrating AI insights into actionable strategies.
