OpenInfra Days North America 2024 at Indiana University

Traditional network observability methods rely heavily on analytics and dashboards, requiring users to manually sift through extensive data to extract actionable insights. This approach proves challenging in large-scale clusters, where rapid decision-making is crucial. AI/ML offer a solution by automating the decision-making process, leveraging pre-existing human intelligence from historical and real-time data. This presentation examines the core aspects of network observability within virtual infrastructure deployments and explores the applicability of AI/ML on anomaly detection and troubleshooting, showcasing how AI/ML can enhance efficiency and responsiveness in network management.