NVIDIA Data Center GPU Manager

6.8easy start · #18 of 58
in Hardware Monitoring Software

Free to practise onyes
Free trialnot on record
Well documentedyes
Runs where you worknot on record

Runs on api, Linux, self-hosted.

NVIDIA Data Center GPU Manager is ranked #18 of 58 in hardware monitoring software on The Geeks Club, made by NVIDIA Data Center GPU Manager (Santa Clara, California, United States). It runs on API, Linux, Self-hosted. There is a free plan.

NVIDIA Data Center GPU Manager plans and pricing

All plans

DCGM open-source product Free Foundational libraries and building blocks are open source; some features, including diagnostics and tests, remain proprietary. developer.nvidia.com · 4 Oct 2026

Compared on hardware monitoring software

Supported platforms: Linux on x86_64 and aarch64 (sbsa); bare-metal or full-passthrough virtualized environments
Remote monitoring: Yes
Alert channels: console, file, callback
Custom sensor support: Yes

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The record

Free plan: Yes
Purpose: DCGM provides tools for managing and monitoring NVIDIA data center GPUs in cluster environments.
Health and diagnostics: It includes active health monitoring, diagnostics, system alerts, and power and clock management policies.
Telemetry: DCGM collects GPU telemetry to help explain job behavior, utilization, and application performance issues.
Low overhead: Its active health monitoring is described as low-overhead and non-invasive while jobs run.
Kubernetes and Prometheus: DCGM-Exporter provides GPU telemetry in Kubernetes environments, and NVIDIA lists out-of-the-box integration with Prometheus.
Other integrations: NVIDIA lists Bright Cluster Manager and IBM Spectrum LSF among its integrations with management and scheduling tools.
APIs: The installer packages include C and Python API examples, and NVIDIA links to open-source Go bindings.
Operating modes: DCGM can run as a service through HostEngine or be incorporated directly into a standalone application.
Operating system and architecture: The product page lists Linux support for x86_64 and aarch64 (sbsa).
GPU support: The current getting-started guide lists NVIDIA Kepler and newer data center GPUs, plus Maxwell and newer non-data-center GPUs, with some feature availability varying by GPU class.
Deployment requirements: The getting-started guide specifies at least 16 GB of host memory and a minimum number of CPU cores equal to the number of GPUs.
Security limitation: DCGM does not add authentication, authorization, or encryption to its TCP protocol, and NVIDIA advises keeping TCP access on a trusted management network.
Intended users: NVIDIA describes infrastructure teams using DCGM standalone or integrating it with cluster management, scheduling, and monitoring products.
Price from: Free

Where it ranks on The Geeks Club

Best Hardware Monitoring Software in 2026#18 of 58

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Sources

developer.nvidia.com/dcgm· checked 24 Sept 2026
docs.nvidia.com/datacenter/dcgm/latest/user-guide/getti· checked 4 Oct 2026
docs.nvidia.com/datacenter/dcgm/latest/learn/getting-st· checked 4 Oct 2026