https://github.com/mindprince/nvidia_gpu_prometheus_exporter
NVIDIA GPU Prometheus Exporter
https://github.com/mindprince/nvidia_gpu_prometheus_exporter
gpu monitoring nvidia-smi nvml prometheus prometheus-exporter
Last synced: about 2 months ago
JSON representation
NVIDIA GPU Prometheus Exporter
- Host: GitHub
- URL: https://github.com/mindprince/nvidia_gpu_prometheus_exporter
- Owner: mindprince
- License: apache-2.0
- Created: 2018-05-20T10:24:27.000Z (about 7 years ago)
- Default Branch: master
- Last Pushed: 2021-07-15T07:41:19.000Z (almost 4 years ago)
- Last Synced: 2024-11-05T22:41:16.071Z (7 months ago)
- Topics: gpu, monitoring, nvidia-smi, nvml, prometheus, prometheus-exporter
- Language: Go
- Size: 285 KB
- Stars: 223
- Watchers: 7
- Forks: 78
- Open Issues: 11
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
NVIDIA GPU Prometheus Exporter
------------------------------
This is a [Prometheus Exporter](https://prometheus.io/docs/instrumenting/exporters/) for
exporting NVIDIA GPU metrics. It uses the [Go bindings](https://github.com/mindprince/gonvml)
for [NVIDIA Management Library](https://developer.nvidia.com/nvidia-management-library-nvml)
(NVML) which is a C-based API that can be used for monitoring NVIDIA GPU devices.
Unlike some other similar exporters, it does not call the
[`nvidia-smi`](https://developer.nvidia.com/nvidia-system-management-interface) binary.
## Building
The repository includes `nvml.h`, so there are no special requirements from the
build environment. `go get` should be able to build the exporter binary.
```
go get github.com/mindprince/nvidia_gpu_prometheus_exporter
```
## Running
The exporter requires the following:
- access to NVML library (`libnvidia-ml.so.1`).
- access to the GPU devices.
To make sure that the exporter can access the NVML libraries, either add them
to the search path for shared libraries. Or set `LD_LIBRARY_PATH` to point to
their location.
By default the metrics are exposed on port `9445`. This can be updated using
the `-web.listen-address` flag.
## Running inside a container
There's a docker image available on Docker Hub at
[mindprince/nvidia_gpu_prometheus_exporter](https://hub.docker.com/r/mindprince/nvidia_gpu_prometheus_exporter/)
If you are running the exporter inside a container, you will need to do the
following to give the container access to NVML library:
```
-e LD_LIBRARY_PATH=
--volume :
```
And you will need to do one of the following to give it access to the GPU
devices:
- Run with `--privileged`
- If you are on docker v17.04.0-ce or above, run with `--device-cgroup-rule 'c 195:* mrw'`
- Run with `--device /dev/nvidiactl:/dev/nvidiactl /dev/nvidia0:/dev/nvidia0 /dev/nvidia1:/dev/nvidia1 `
If you don't want to do the above, you can run it using nvidia-docker.
## Running using [nvidia-docker](https://github.com/NVIDIA/nvidia-docker)
```
nvidia-docker run -p 9445:9445 -ti mindprince/nvidia_gpu_prometheus_exporter:0.1
```