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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 DCGM telemetry; Prometheus scrapes and stores it, while Grafana displays it. For AMD GPUs, AMD’s older SMI Exporter is marked unmaintained, and the compatibility of its named replacement should be checked for your hardware before deployment.
Which GPU monitoring tool should you choose?
| Tool or layer | Best fit | What it does | Important limitation |
|---|---|---|---|
| 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 paths. NVIDIA DCGM Exporter installation guide | The GPU, driver, and DCGM combination must be supported. Exporter and DCGM versions need to be paired using NVIDIA’s compatibility guidance. |
| Prometheus and Grafana | Collecting, retaining, visualizing, and alerting on exporter metrics | Prometheus scrapes and stores time-series data; Grafana visualizes it. NVIDIA documents a GPU monitoring stack and provides a Grafana dashboard. NVIDIA DCGM Exporter installation guide DCGM 3.1 telemetry documentation | These are stack components, not GPU telemetry collectors by themselves. Alert management is handled by Prometheus Alertmanager in NVIDIA’s documented stack. |
| AMD SMI Exporter | Reference for the legacy AMD Prometheus exporter | Its repository describes AMD CPU and datacenter GPU metrics through AMDSMI. AMD SMI Exporter repository | AMD says it will no longer receive updates and points to AMD Device Metrics Exporter as its replacement. The replacement’s current hardware and software coverage is not established in the cited documentation. |
nvidia-smi |
Initial host-level NVIDIA GPU and driver discovery during troubleshooting | NVIDIA identifies it as a diagnostic check to run before troubleshooting DCGM Exporter. NVIDIA DCGM Exporter installation guide | It is a command-line diagnostic, not a time-series monitoring stack. |
Choose based first on the GPU vendor and model, then on whether the server runs a Linux service, containers, or Kubernetes. Also check the driver and runtime combination, the telemetry fields you need, whether metrics must map to workloads or pods, and how metrics will be scraped, retained, visualized, and alerted on.
How the NVIDIA monitoring stack fits together
DCGM Exporter is the collection endpoint in this setup. It exposes selected GPU telemetry in Prometheus format. Prometheus scrapes and stores those metrics, and Grafana turns them into dashboards. NVIDIA also documents Prometheus Alertmanager for managing alerts and supplies a Grafana dashboard with Prometheus as its data source. DCGM 3.1 telemetry documentation
For Kubernetes, NVIDIA describes DCGM Exporter as using the KubeletPodResources API and exposing metrics for Prometheus to scrape. That makes it relevant when operators need GPU metrics associated with Kubernetes workloads, rather than only a host-level diagnostic view.
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Ways to deploy DCGM Exporter on Linux
NVIDIA’s installation guide describes several deployment patterns. Use the one that matches how GPU drivers and monitoring are managed on the server; do not assume that an example command is safe to copy unchanged into production. NVIDIA DCGM Exporter installation guide
Install it as a Linux service
The documented package is datacenter-gpu-manager-exporter. NVIDIA describes apt-based installation for Ubuntu and Debian, and dnf for RHEL-compatible distributions. The package runs as systemd-managed services, making this route suitable for a GPU host managed directly through the operating system.
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Run a standalone container
NVIDIA’s example exposes exporter port 9400 and uses --gpus all plus the SYS_ADMIN capability to expose GPUs and profiling fields. Those flags have security implications: review Docker privilege and Linux capability guidance, and adapt access to the minimum required by your deployment. Confirm that the exporter can access the host driver and that Prometheus can reach its metrics endpoint.
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NVIDIA’s Helm chart creates an exporter pod on each selected GPU node. If Prometheus Operator custom resource definitions are not installed in the cluster, NVIDIA says to disable the chart’s ServiceMonitor option. Check that node selection, Prometheus scraping, and any workload-mapping needs align with the cluster’s configuration.
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Use GPU Operator when it already manages the stack
NVIDIA also documents deployment through GPU Operator, which can manage the driver, container toolkit, DCGM, exporter, and related Kubernetes resources. This can avoid managing overlapping components separately, but the operator’s supported GPU and software combination still needs to match the target system.
AMD GPU monitoring: check the replacement’s support first
The AMD SMI Exporter repository describes a Prometheus exporter for AMD CPU and datacenter GPU metrics using AMDSMI, but explicitly says the project will no longer receive updates. It directs users to AMD Device Metrics Exporter as the official replacement. AMD SMI Exporter repository
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That notice does not establish which AMD GPU models, AMDSMI or ROCm versions, or Linux distributions the replacement supports. Before adopting it, verify current coverage in the replacement project’s official documentation for the exact server hardware and software stack. The legacy repository is useful for understanding the older exporter, not as a maintained deployment recommendation.
Deployment checks before relying on GPU metrics
- Confirm hardware and driver support. For DCGM Exporter, verify that the NVIDIA GPU, driver, and DCGM versions are supported together; use NVIDIA’s compatibility documentation to pair exporter and DCGM versions.
- Match deployment to the environment. Decide between a system package, standalone container, Helm chart, or GPU Operator based on how the host or cluster manages drivers and services.
- Check endpoint access. The exporter must be able to access the GPU through the driver, and Prometheus must be able to reach the exporter’s metrics endpoint. Treat port 9400 as the port used in NVIDIA’s example, not a guarantee that every deployment uses the same network configuration.
- Review permissions. Do not copy broad container capabilities into production without assessing their security implications and whether they are needed for the telemetry fields you intend to expose.
- Validate the scrape and dashboard path. Ensure Prometheus is scraping the exporter, Grafana uses the correct Prometheus data source, and any alerting rules are connected to the alert-management setup you operate.
What to verify before production use
NVIDIA’s installation guide was accessed on October 9, 2026. The separate telemetry page cited here is for DCGM 3.1, so use it for architecture context rather than assuming its version-specific details apply to every current release. Confirm current release compatibility and supported hardware in NVIDIA’s documentation before installing. NVIDIA DCGM Exporter installation guide DCGM 3.1 telemetry documentation
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