mindprince / Nvidia_gpu_prometheus_exporter
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NVIDIA GPU Prometheus Exporter
This is a Prometheus Exporter for
exporting NVIDIA GPU metrics. It uses the Go bindings
for NVIDIA Management Library
(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 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
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=<path-where-nvml-is-present>
--volume <above-path>:<above-path>
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 <and-so-on-for-all-nvidia-devices>
If you don't want to do the above, you can run it using nvidia-docker.
Running using nvidia-docker
nvidia-docker run -p 9445:9445 -ti mindprince/nvidia_gpu_prometheus_exporter:0.1