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How-to Guides

GPU Monitoring

Monitor NVIDIA GPU utilization, memory, and costs across your Kubernetes clusters.

Last updated

If DCGM Exporter is running in your cluster, Kubeadapt collects GPU metrics with zero configuration. The agent discovers it automatically.

Supported GPUs

GPU VendorExporter RequiredStatus
NVIDIA (A100, H100, V100, T4, L4, P100, and any DCGM-compatible GPU)DCGM ExporterSupported
AMD (MI250, MI300)-Not supported
Intel (Gaudi, Flex)-Not supported

Prerequisites

Check the Dashboard

Sign in to app.kubeadapt.io and navigate to your cluster. GPU nodes display:

  • GPU count per node
  • GPU model name (e.g., "NVIDIA A100-SXM4-80GB")
  • GPU utilization percentage
  • GPU memory usage

GPU Sharing Limitations

Configuration

GPU metrics collection is enabled by default:

yaml
agent:
  config:
    gpuMetricsEnabled: true # default
    dcgmPort: 9400 # default
    dcgmNamespace: "" # auto-detect across all namespaces

Override Namespace

If the agent cannot find DCGM Exporter pods, restrict the search to a specific namespace:

bash
helm upgrade kubeadapt kubeadapt/kubeadapt \
  --namespace kubeadapt \
  --reuse-values \
  --set agent.config.dcgmNamespace="gpu-operator"

Disable GPU Metrics

yaml
agent:
  config:
    gpuMetricsEnabled: false

For the full list of Helm values, see the kubeadapt-helm chart on GitHub.

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