# Infrastructure Monitoring The host organization is responsible for monitoring the health and performance of the NVIDIA Run:ai control plane and the underlying Kubernetes infrastructure. This ensures system stability, availability, and operational compliance across all tenant environments. ## What to Monitor Monitoring focuses on three main infrastructure layers: * **Control plane and cluster services** - This includes the NVIDIA Run:ai system components running in Kubernetes pods. The host organization must ensure these services are healthy and performant to maintain platform availability. * **Kubernetes Cluster** - Monitor the overall state of the Kubernetes environment, including node health, API server availability, and core services. For general cluster guidance, refer to the [official Kubernetes documentation](https://kubernetes.io/docs/tasks/debug/debug-cluster/resource-usage-monitoring/).. * **Host Infrastructure** - This represents the physical or virtual machines that host the Kubernetes nodes. The host organization is responsible for maintaining system-level health (CPU, memory, storage), OS patches, and networking. NVIDIA Run:ai does not require any special configurations at this level. ## Recommended Monitoring Setup with Grafana The host organization is responsible for monitoring the health and performance of the NVIDIA Run:ai control plane and the underlying Kubernetes infrastructure. We recommend using Grafana with Prometheus as the data source. Grafana offers a wide selection of prebuilt dashboards that provide insight into the control plane, cluster services, and node-level behavior. Recommended dashboards include: * **Kubernetes Cluster Monitoring** - Tracks overall cluster health, resource utilization, and node availability. * **Node Exporter Full** - Displays detailed system-level metrics for each node (CPU, memory, disk, etc.). * **Kubelet Metrics** - Monitors node-pod interactions and kubelet performance. * **Kubernetes Resource Requests vs Limits** - Visualizes the gap between requested vs. actual resource usage for improved capacity planning. These dashboards are available through the Grafana community and can be easily imported by ID. They help host organizations maintain observability across the multi-tenant control plane and ensure infrastructure-level SLAs are met. --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://run-ai-docs.nvidia.com/multi-tenant/2.24/infrastructure-setup/procedures/monitoring.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.