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Best Open-Source GPU Monitoring Tools for Linux Servers

For NVIDIA Linux servers, DCGM Exporter is the documented path to GPU metrics in Prometheus and Grafana. AMD users should verify current support for the replacement exporter.
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For Linux servers with NVIDIA GPUs, NVIDIA DCGM Exporter is the strongest-supported starting point in the available official documentation when you want GPU metrics in Prometheus and dashboards in Grafana. It exports selected telemetry; Prometheus scrapes and stores it, and Grafana displays it. AMD’s older SMI exporter is no longer maintained, and its repository points to AMD Device Metrics Exporter as its replacement, but the replacement’s hardware and software coverage needs checking before deployment.

Which GPU monitoring tool should you choose?

Start with the GPU vendor and the server’s driver and runtime support, then choose how to deploy and collect the metrics. A dashboard preference cannot compensate for an unsupported GPU or driver combination.

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Tool or layer Best fit Role Important caveat
NVIDIA DCGM Exporter NVIDIA GPU hosts, including Kubernetes fleets using Prometheus Exports selected DCGM telemetry in Prometheus format. NVIDIA documents package, container, Helm, and GPU Operator deployment routes. The GPU, driver, and DCGM combination must be supported. Pair exporter and DCGM versions using NVIDIA’s compatibility documentation.
Prometheus and Grafana Historical metrics, dashboards, and alerting around exporters Prometheus scrapes and stores metrics; Grafana visualizes them. NVIDIA documents a GPU monitoring stack and provides a Grafana dashboard. These are stack components, not GPU telemetry collectors by themselves.
AMD SMI Exporter Reference for a legacy AMD Prometheus exporter The repository describes AMD CPU and datacenter GPU metrics through AMDSMI. AMD says the project will no longer receive updates and names AMD Device Metrics Exporter as its replacement. Verify the replacement’s current compatibility before choosing it.
nvidia-smi Initial NVIDIA host-level troubleshooting Useful for checking GPU and driver visibility while diagnosing a host. It is a command-line diagnostic, not a time-series monitoring stack.

What NVIDIA DCGM Exporter provides

DCGM Exporter exposes selected telemetry from NVIDIA’s Data Center GPU Manager (DCGM) in a format Prometheus can scrape. For Kubernetes, NVIDIA describes the exporter as using the KubeletPodResources API and exposing metrics for Prometheus scraping. Workload or pod mapping can therefore be a relevant selection criterion when monitoring a cluster.

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NVIDIA’s installation guide recommends: “Install one exporter on each GPU node that Prometheus should monitor.” This makes the exporter a per-node collector rather than a central GPU metrics service.

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Choose the deployment that matches the server

Linux service on a host

NVIDIA documents installing the datacenter-gpu-manager-exporter package, which is managed as systemd services. The guide shows apt for Ubuntu and Debian, and dnf for RHEL-compatible systems. Confirm that the GPU, driver, DCGM, and distribution combination is supported before installing.

Standalone container

A container can run on each GPU host. NVIDIA’s example exposes port 9400 and uses --gpus all and the SYS_ADMIN capability to expose GPUs and profiling fields. Treat this as an example, not a production-ready security policy: review the container privileges and Linux capabilities, driver access, network exposure, and version compatibility for your environment.

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Kubernetes Helm chart

NVIDIA’s Helm chart creates an exporter pod on each selected GPU node. The guide says to disable the chart’s ServiceMonitor when Prometheus Operator custom resource definitions are not installed. Check how your Prometheus deployment discovers scrape targets before enabling that resource.

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GPU Operator

If the NVIDIA GPU Operator already manages components such as the driver, container toolkit, DCGM, and exporter, use that existing lifecycle rather than layering an independent exporter deployment over it. Confirm the operator’s support for your hardware and cluster configuration.

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Build the metrics pipeline around the exporter

  1. Check host visibility. On an NVIDIA server, use nvidia-smi as an initial diagnostic to confirm that the host sees the GPU and driver before troubleshooting DCGM Exporter.
  2. Deploy the exporter on monitored GPU nodes. Choose the host service, container, Helm chart, or GPU Operator route that fits your infrastructure.
  3. Make metrics reachable by Prometheus. Confirm the exporter endpoint is exposed only as intended and that Prometheus can reach and scrape it. NVIDIA’s container example uses port 9400.
  4. Visualize and alert. Configure Grafana with Prometheus as its data source and use NVIDIA’s supplied DCGM dashboard if it suits your needs. NVIDIA identifies Prometheus Alertmanager for managing alerts.

The exporter gathers and exposes telemetry; it does not itself provide the full history, dashboards, or alert workflow. Those depend on the surrounding monitoring stack and its configuration.

How to assess AMD support

Do not treat the older AMD SMI Exporter repository as a maintained recommendation: it says the project will no longer receive updates and directs users to AMD Device Metrics Exporter. The available evidence does not establish which GPU models, AMDSMI or ROCm versions, or Linux distributions the replacement supports. Check AMD’s current compatibility information for your exact system before building a deployment around it.

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Selection checklist

  • Confirm GPU vendor and model, supported driver, and the exporter’s required telemetry library or runtime.
  • Choose host service, container, or Kubernetes deployment based on who manages drivers and monitoring components.
  • Identify the metrics you need and whether workload or pod attribution matters.
  • Check project maintenance status and version compatibility, not just whether an exporter once worked on similar hardware.
  • Plan where Prometheus scrapes and retains data, how Grafana dashboards will be configured, and how alerts will be handled.

NVIDIA’s installation guide, accessed October 9, 2026, is the primary deployment reference here. Its DCGM telemetry documentation reviewed for architecture context is identified as DCGM 3.1 documentation, so verify current release compatibility rather than assuming version-specific details carry forward.

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