This component monitors new Pods on a node and publishes CPU/MEM/GPU utilization stats to a queue. It runs as a daemonset on each node. Using the NVML library it reports detailed GPU statistics like temperature and power consumption.
RiseML welcomes contributions from all developers. The high level process for development matches many other open source projects. See below for an outline.
Please check config.py. It contains all environment variables used.
The following information is sent on startup:
{
"name":"ip-172-31-30-80",
"gpus":[
{
"name":"Tesla V100-SXM2-16GB",
"mem":16936861696,
"serial":"0322917092147",
"device":"/dev/nvidia0"
}
],
"memory":62879860000,
"cpus":4,
"nvidia_driver":"384.90",
"cpu_model":"Intel(R) Xeon(R) CPU E5-2686 v4 @ 2.30GHz"
}
The following messages are sent while a POD is running:
GPU utilization:
{
"job_id":"0408f010-bb08-11e7-965a-0a580af4f059",
"gpus":{
"/dev/nvidia0":{
"temperature":60,
"power_limit":249,
"memory_utilization":31,
"gpu_utilization":67,
"memory_free":520421376,
"name":"Tesla V100-SXM2-16GB",
"device_minor":0,
"power_draw":107,
"memory_total":16936861696,
"device_bus_id":"0000:00:1E.0",
"fan_speed":null,
"memory_used":11475156992
}
},
"timestamp":1509103012437
}
CPU/memory utilization:
{
"job_id":"0408f010-bb08-11e7-965a-0a580af4f059",
"percpu_percent":[
96.71262123755025,
97.95838776488651,
95.34449857171664,
95.66360231475599
],
"memory_limit":64388976640,
"timestamp":1509103012109,
"memory_used":1828540416,
"cpu_percent":385.6786764857881
}
Content type
Image
Digest
Size
95.7 MB
Last updated
over 8 years ago
docker pull riseml/monitor