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What DCGM Exporter exposes—and what it does not
NVIDIA Data Center GPU Manager (DCGM) provides the host engine, tools, libraries, diagnostics, field definitions, and interfaces for GPU management. DCGM Exporter is a separate component: it turns selected DCGM fields into Prometheus metrics at an HTTP endpoint. By default, it uses an embedded host engine; it can also connect to a separately managed engine. See NVIDIA’s DCGM Exporter documentation.
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A remote Prometheus server must be able to reach that endpoint. NVIDIA lists access from Prometheus to the exporter as a requirement when the scraper is on another host or cluster. That requirement does not mean the endpoint should be open to every network or user. Permit only the intended monitoring path, then use endpoint protections as an additional layer.
Secure the metrics endpoint
Protect HTTP access with TLS or authentication
Configure DCGM Exporter’s --web-config-file option with a Prometheus exporter-toolkit web configuration file. NVIDIA documents this option for enabling TLS or basic authentication; it is unset by default. The configuration applies to the root, health, metrics, and enabled pprof endpoints, rather than only /metrics. Consult the exporter command reference and the NVIDIA installation guide for the deployment-specific command and setup.
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Choose TLS, authentication, or both according to the trust boundary between the exporter and scraper. Avoid treating a private address or firewall rule as a substitute for protecting the HTTP service: network restriction and endpoint security address different risks.
Restrict network reachability
- Identify the Prometheus instance or trusted monitoring network that will scrape the exporter, including its source addresses and route to the GPU host.
- Allow access to the exporter listener only from that source or network. Keep the documented default port,
9400, closed to unrelated hosts; if you configure a different listener, apply the same narrow policy to it. - Configure Prometheus to scrape the protected endpoint using the matching TLS or authentication settings, then test from the scraper’s actual network location.
The narrow allow-list is a security recommendation based on NVIDIA’s documented remote-scraping requirement; it is not a special DCGM feature.
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Limit the metrics you collect
Configure the collector CSV or YAML to select the DCGM fields you need for monitoring rather than exporting every available field by default. Field selection can reduce unnecessary telemetry, but it does not replace access control for the endpoint. NVIDIA documents collector configuration in its installation and configuration guide.
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NVIDIA documents package-managed systemd, a standalone OCI container, and Kubernetes deployments managed with Helm or GPU Operator. These are different lifecycle choices, not evidence of different measured performance. Check the current DCGM product support matrix and compatibility requirements for the GPU, driver, DCGM version, and runtime before deploying.
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| Deployment | Operational detail | Security consideration |
|---|---|---|
| Package-managed service | Run and manage the exporter as a system service on the GPU host; it can use the embedded host engine or connect to a separately managed one. | Apply endpoint configuration and host firewall rules to the service’s listener. Keep the engine’s own access appropriate to its management model. |
| Standalone container | The host needs GPU access through the NVIDIA Container Toolkit. Review NVIDIA’s documented container example before adapting it. | Inspect GPU access, published ports, runtime permissions, and the example’s --cap-add SYS_ADMIN capability. Grant only what the deployment needs, and do not expose the published port broadly. |
| Kubernetes | Use NVIDIA’s Helm chart or GPU Operator management where appropriate. GPU Operator can manage DCGM Exporter as part of the broader GPU software stack. | Configure access through the cluster’s service and network controls. When GPU Operator owns the exporter DaemonSet, use its supported configuration path rather than editing the managed DaemonSet directly. |
For Kubernetes setup and component ownership, consult NVIDIA’s GPU Operator documentation and GPU telemetry guide. NVIDIA’s documented Kubernetes approach pairs DCGM Exporter with Prometheus-compatible monitoring; Grafana can be used for visualization.
Protect surfaces beyond /metrics
Metrics are not the only data or control surface associated with an exporter deployment. NVIDIA’s documentation identifies runtime sockets, debug-dump directories, and profiling endpoints as areas to protect.
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- Runtime sockets: Avoid mounting a privileged Docker-compatible runtime socket unless operationally necessary. Access to it can expose privileged runtime metadata; do not make it available to untrusted workloads or users.
- Debug dumps: Restrict access to dump storage and retain dumps only as needed. They can contain device and workload metadata.
- Profiling endpoints: Do not enable pprof endpoints without a clear diagnostic need. If enabled, they are covered by the exporter web configuration, so protect them with the same TLS or authentication controls and network restrictions.
Verify the setup without widening access
- From the GPU host, request the local exporter metrics endpoint and confirm that expected metric names beginning with
DCGM_appear. - From the Prometheus host or its actual network path, confirm that the configured scraper can reach and authenticate to the endpoint.
- Check that a host outside the intended monitoring path cannot connect, and that the exporter’s root, health, metrics, and any enabled profiling endpoints are protected.
- For Kubernetes, NVIDIA documents port-forwarding the Service as a way to verify the endpoint without making it generally reachable. Follow the current verification steps in the NVIDIA installation guide.
If local verification succeeds but remote scraping fails, check the listener address, route and firewall rules, and Prometheus TLS or authentication configuration. If metrics are missing, review the selected collector fields and confirm that the GPU, driver, DCGM, and runtime combination is supported.
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