ICINGA
Open-source monitoring with scalable architecture and flexible alerting
ABOUT
Monitoring infrastructure for AI systems requires checking diverse components — REST API endpoints on model servers, GPU utilization on training nodes, queue depths on data pipelines — each with different check intervals and notification policies. Traditional monitoring tools struggle with the scale and complexity of modern distributed AI environments. Icinga solves this with a modular monitoring engine that supports distributed and high-availability setups, a powerful domain-specific language for defining check configurations, role-based permissions for multi-team environments, and extensive graphing and reporting capabilities built on IDO (Icinga Data Output) database backend.