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@wolph
Last active December 18, 2023 10:27
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This prometheus exports all of your AIDA64 data to a Prometheus server so you can chart all of them using Grafana: https://grafana.com/grafana/dashboards/11339
import re
import mmap
import typing
import hashlib
import logging
import argparse
import datetime
import ipaddress
import dataclasses
import xml.etree.cElementTree as ET
import prometheus_client
from prometheus_client import core
from prometheus_client import exposition
PREFIX = 'aida'
IGNORED_IDS = {'sdate', 'stime', 'stimens', 'suptimens', 'smemspeed',
'sgpu1bustyp', 'sgpu1perfcap', 'sgpu2bustyp', 'sgpu2perfcap'}
ID_LABEL_REWRITES = [
(re.compile(r'^(t)([a-z]+)$'), r'temp-\2', ['type']),
(re.compile(r'^(vdimm)(\w+)$'), r'\1-\2', ['bank']),
(re.compile(r'^(snic)(\d+)(tot)(\w+)$'), r'\1\3-\2-\4',
['nic', 'direction']),
(re.compile(r'^(snic)(\d+)(\w+)(rate)$'), r'\1\4-\2-\3',
['nic', 'direction']),
(re.compile(r'^(snic)(\d+)(connspd)$'), r'\1\3-\2', ['nic']),
(re.compile(r'^(scpu)(\d+)(\w+)$'), r'\1c\3-\2', ['core']),
(re.compile(r'^(tcc|scc)'), r'\1', ['cpu', 'core']),
(re.compile(r'^(sdsk)(\d+)(\w+)$'), r'\1-\2-\3', ['disk', 'type']),
(re.compile(r'^(tpcie)(\d+)$'), r'\1-\2', ['slot']),
(re.compile(r'^t(temp)(\d+)$'), r'\1-\2', ['sensor']),
(re.compile(r'^(thdd)(\d+)(ts)(\d+)$'), r'\1\3-\2-\4', ['disk', 'sensor']),
(re.compile(r'^(thdd)(\d+)$'), r'\1-\2', ['disk']),
(re.compile(r'^(fcha)(\d+)$'), r'\1-\2', ['fan']),
(re.compile(r'^s(\w*mem)(uti)$'), r'mem\2-\1', ['type']),
(re.compile(r'^s(\w*mem)$'), r'mem-\1', ['type']),
(re.compile(r'^(sdrv)(\w+)(free|used)(spc)$'),
r'\1\4-\2-\3', ['drive', 'type']),
(re.compile(r'^(sdrv)(\w+)(spc|uti)$'),
r'\1\3-\2', ['drive', 'type']),
# (re.compile(r'^(sgpu)(\d)(\w+)(uti)$'),
# r'\1\4-\2-\3', ['gpu', 'type']),
(re.compile(r'^([stfdvp]gpu)(\d+)(\w*?)(uti|)$'), r'\1\4-\2-\3', ['gpu',
'type']),
(re.compile(r'^(f)(\w+)$'), r'fan-\2', ['type']),
(re.compile(r'^(v)(\w+)$'), r'volt-\2', ['type']),
(re.compile(r'^(p)(\w+)$'), r'pwr-\2', ['type']),
(re.compile(r'^(s)(\w+)clk$'), r'clk-\2', ['type']),
]
@dataclasses.dataclass
class Measurement:
# Nearly all metrics are gauges but some special ones are better suited
# as counter or histograms
MetricFamily = core.GaugeMetricFamily
group: str
id_: id
documentation: str
raw_value: str
values: typing.List[float] = dataclasses.field(default_factory=list)
labels: typing.List[str] = dataclasses.field(default_factory=list)
label_values: typing.List[typing.List[str]] = dataclasses.field(
default_factory=list)
@classmethod
def from_element(cls, elem):
group = elem.tag
id_ = elem.find('id').text.lower()
documentation = elem.find('label').text
raw_value = elem.find('value').text
return Measurement(group=group, id_=id_,
documentation=documentation, raw_value=raw_value)
def __post_init__(self):
# Try to break early if this id is ignored
if self.id_ in IGNORED_IDS:
return
for search, replace, labels in ID_LABEL_REWRITES:
self.id_, changes = search.subn(replace, self.id_)
if not changes:
continue
self.id_, *label_values = self.id_.split('-')
self.label_values = [label_values + [self.documentation]]
self.labels = labels + ['documentation']
# Parse values if `self.parse_{id_}` is available and falls back to
# `self.parse` alternatively
parser_name = 'parse_' + self.id_.split('-')[0]
parser = getattr(self, parser_name, self.parse)
logging.debug('Parsing %r using %r', self, parser)
parser()
@property
def key(self):
key = '_'.join((PREFIX, self.group, self.id_))
key_parts = []
seen = set()
for part in key.split('_'):
if part in seen:
continue
else:
key_parts.append(part)
seen.add(part)
return '_'.join(key_parts)
def get_metric(self):
return self.MetricFamily(self.key, self.documentation, labels=self.labels)
def parse(self):
try:
self.values.append(float(self.raw_value))
except (TypeError, ValueError):
logging.warning('Incorrect value for %r', self)
def parse_suptime(self):
self.MetricFamily = core.CounterMetricFamily
parts = self.raw_value.split()
if parts[1:]:
# days is in 123d format, this strips the `d`
days = int(parts[0].rstrip('d'))
else:
days = 0
hours, minutes, seconds = map(int, parts[-1].split(':'))
uptime = datetime.timedelta(days=days, hours=hours, minutes=minutes,
seconds=seconds)
self.values.append(uptime.total_seconds())
def parse_sdramfsb(self):
numerator, denominator = map(int, self.raw_value.split(':'))
self.values.append(numerator / denominator)
def parse_smemtim(self):
self.labels = ['CL', 'tRCD', 'tRP', 'tRAS', 'CMD']
self.label_values = [re.split(r'[^\d]', self.raw_value)]
def parse_sdeskres(self):
self.labels = ['dimension']
self.label_values = [['width'], ['height']]
width, height = self.raw_value.split(' x ')
self.values = [int(width), int(height)]
def parse_ssmasta(self):
if self.raw_value == 'OK':
value = 0
else:
# Convert the smart status into a unique repeatable number
value = int(hashlib.sha1(self.raw_value).hexdigest(), 16) % (2**31)
self.values.append(value)
def parse_sslista(self):
if self.raw_value.lower() == 'disabled':
self.values.append(0)
else:
self.values.append(1)
def parse_spriipaddr(self):
self.values.append(int(ipaddress.ip_address(self.raw_value)))
parse_sextipaddr = parse_spriipaddr
# Uses strings instead of numbers in many cases
def parse_sbatt(self):
if self.raw_value.lower().isdigit():
self.values.append(int(self.raw_value))
class AidaCollector:
def __init__(self, address='AIDA64_SensorValues'):
self.length = None
self.address = address
def read(self):
# Make sure to only run the idiocy below once
if self.length:
data = mmap.mmap(0, self.length, self.address).read()
else:
# Don't ask... bloody Windows gives permission denied if you read
# beyond the mmap size but doesn't give a method to find out how
# large it is
for length in range(32768, 0, -1024):
try:
self.length = length
data = mmap.mmap(0, self.length, self.address).read()
break
except OSError as e:
pass
return data.strip(b'\x00')
def collect(self):
metrics = dict()
for element in ET.fromstring('<root>%s</root>' % self.read()):
measurement = Measurement.from_element(element)
if measurement.id_ in IGNORED_IDS:
logging.debug('Ignoring %s', measurement)
continue
if not measurement.values:
continue
if measurement.key not in metrics:
metrics[measurement.key] = measurement.get_metric()
logging.info(measurement)
if measurement.labels:
for label_values, value in zip(measurement.label_values,
measurement.values):
metrics[measurement.key].add_metric(label_values, value)
else:
for value in measurement.values:
metrics[measurement.key].add_metric([], value)
yield from metrics.values()
def main():
parser = argparse.ArgumentParser()
parser.add_argument('-v', '--verbose', action='count', default=0)
parser.add_argument('-q', '--quiet', action='count', default=0)
parser.add_argument('-p', '--port', type=int, default=9091)
args = parser.parse_args()
verbosity = args.verbose - args.quiet
if verbosity > 1:
level = logging.DEBUG
elif verbosity == 0:
level = logging.INFO
elif verbosity == -1:
level = logging.WARNING
else:
level = logging.ERROR
logging.basicConfig(level=level)
registry = prometheus_client.CollectorRegistry()
registry.register(AidaCollector())
if level:
exposition.generate_latest(registry)
MetricsHandler = prometheus_client.MetricsHandler.factory(registry)
httpd = exposition.ThreadingWSGIServer(('', args.port), MetricsHandler)
httpd.serve_forever()
if __name__ == '__main__':
main()
{
"aliasColors": {},
"bars": false,
"dashLength": 10,
"dashes": false,
"datasource": "Prometheus",
"fill": 0,
"fillGradient": 0,
"gridPos": {
"h": 9,
"w": 12,
"x": 12,
"y": 27
},
"id": 8,
"legend": {
"alignAsTable": true,
"avg": false,
"current": false,
"max": false,
"min": false,
"rightSide": true,
"show": true,
"total": false,
"values": false
},
"lines": true,
"linewidth": 1,
"nullPointMode": "null",
"options": {
"dataLinks": []
},
"percentage": false,
"pointradius": 2,
"points": false,
"renderer": "flot",
"seriesOverrides": [
{
"alias": "/Activity$/",
"yaxis": 2
}
],
"spaceLength": 10,
"stack": false,
"steppedLine": false,
"targets": [
{
"expr": "aida_sys_sdsk{instance=~\"$instance\"}",
"legendFormat": "{{instance}} {{documentation}}",
"refId": "A"
}
],
"thresholds": [],
"timeFrom": null,
"timeRegions": [],
"timeShift": null,
"title": "Disk Activity",
"tooltip": {
"shared": true,
"sort": 0,
"value_type": "individual"
},
"type": "graph",
"xaxis": {
"buckets": null,
"mode": "time",
"name": null,
"show": true,
"values": []
},
"yaxes": [
{
"format": "MBs",
"label": "",
"logBase": 1,
"max": null,
"min": null,
"show": true
},
{
"format": "percent",
"label": null,
"logBase": 1,
"max": "100",
"min": "0",
"show": true
}
],
"yaxis": {
"align": false,
"alignLevel": null
}
}
@corgan2222
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corgan2222 commented Jan 19, 2021

Thanxs for this!! This was excactly what i was looking for!

After hours to find out how to run prometheus on docker/windows, i got it running.
Maybe you want to put this into your discription how to get this running for people like me, which never touched prometheus.

create a prometheus.yml somewhere on your disk
change the ip:port that match to your system. For me, 127.0.0.1 did not work, so i used the ip of my system.

global:
  scrape_interval: 5s
  external_labels:
    monitor: 'local-monitor'

scrape_configs:
  - job_name: 'aida'
    static_configs:
      - targets: ['192.168.2.30:9091']

then open command promt with wsl2/docker running
change the path c:\tmp\prometheus.yml to the path to your prom.yml

docker run -p 9090:9090 -v c:\tmp\prometheus.yml:/etc/prometheus/prometheus.yml --name=prometheus prom/prometheus --config.file=/etc/prometheus/prometheus.yml

@wolph
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Author

wolph commented Jan 19, 2021

Well... I think your write-up does a great job already :)

This exporter was meant to go together with Grafana using this dashboard: https://grafana.com/grafana/dashboards/11339
If you have Grafana running, you can probably get Prometheus running in a similar/easy way. If you're only running Prometheus right now, I suggest you add Grafana to the mix for pretty charts.

image

@corgan2222
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yes, thanks! The grafana Dashboard Website got me to this gist here. :)
thanks again!

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