feat(observability): per-GPU metrics for the mixed AMD/NVIDIA fleet #61
@@ -40,6 +40,7 @@ SERVICE_ORDER = (
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"alloy",
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"node-exporter",
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"cadvisor",
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"gpu-exporter",
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"alertmanager",
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"authentik-postgres",
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"authentik-server",
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@@ -94,6 +95,7 @@ DANKCLAW_SERVICES = {
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"alloy",
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"node-exporter",
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"cadvisor",
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"gpu-exporter",
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"alertmanager",
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"authentik-postgres",
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"authentik-server",
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@@ -127,6 +129,7 @@ DANKSERVER_SERVICES = {
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"frank-archon",
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"node-exporter",
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"cadvisor",
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"gpu-exporter",
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}
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# FrankBook-Pro runs the *arr stack + qBittorrent inside a podman machine on
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@@ -452,6 +455,12 @@ def services_for_path(path: str, target: str) -> set[str]:
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# change to it redeploying alertmanager is the only path that
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# reaches it on the host.
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_add(services, "alertmanager")
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if name in {"gpu-exporter.py", "gpu-exporter.service"}:
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# The host-process GPU exporter is installed directly by the
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# gpu-exporter deploy on BOTH hosts, so its script and unit select
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# that service (target_services then keeps it only on the host being
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# planned). Editing the collector restarts the running exporter.
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_add(services, "gpu-exporter")
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if name in {"frank-zealot.env", "frank-zealot.service", "serve-frank-zealot.sh"}:
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# llama.cpp frank-zealot (2026-09-16) keeps its unit, env and serve
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# files here; each one selects frank-zealot only. The ik_llama.cpp
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@@ -86,7 +86,7 @@ service_is_allowed() {
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dankclaw:open-webui|dankclaw:gitea-postgres|dankclaw:gitea-server|\
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dankclaw:comfyui|dankclaw:hermes|\
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dankclaw:hermes-dashboard|dankclaw:hermes-webui|dankclaw:prometheus|dankclaw:grafana|\
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dankclaw:loki|dankclaw:alloy|dankclaw:node-exporter|dankclaw:cadvisor|dankclaw:alertmanager|\
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dankclaw:loki|dankclaw:alloy|dankclaw:node-exporter|dankclaw:cadvisor|dankclaw:gpu-exporter|dankclaw:alertmanager|\
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dankclaw:authentik-postgres|dankclaw:authentik-server|\
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dankclaw:authentik-worker|dankclaw:authentik-outpost|dankclaw:authentik-outpost-ldap|dankclaw:anubis|\
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dankclaw:caddy|dankclaw:homepage|dankclaw:seerr|dankclaw:marreta|\
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@@ -97,7 +97,7 @@ service_is_allowed() {
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dankserver:copyparty|dankserver:jellyfin|dankserver:calibre-web|dankserver:calibre-server|dankserver:plex|dankserver:tautulli|\
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dankserver:prowlarr|dankserver:qbittorrent|dankserver:radarr|\
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dankserver:sonarr|dankserver:lidarr|dankserver:readarr|\
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dankserver:frank-archon|dankserver:node-exporter|dankserver:cadvisor|\
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dankserver:frank-archon|dankserver:node-exporter|dankserver:cadvisor|dankserver:gpu-exporter|\
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frankbook-pro:gluetun|frankbook-pro:qbittorrent|frankbook-pro:prowlarr|\
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frankbook-pro:radarr|frankbook-pro:sonarr|frankbook-pro:lidarr|\
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frankbook-pro:readarr)
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@@ -275,6 +275,36 @@ install_signal_relay() {
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return 1
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}
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# Host-process GPU metrics exporter (amdgpu sysfs + nvidia-smi). Not a quadlet:
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# it runs python3 from the checkout on the host so it can read the DRM/cgroup
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# sysfs and shell out to nvidia-smi. Same two-address bind posture as
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# node-exporter/cadvisor (loopback + this host's LAN), so it is never a wildcard.
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deploy_gpu_exporter() {
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local unit_dir="$HOME/.config/systemd/user" lan dropin i
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case "$TARGET" in
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dankclaw) lan=192.168.0.143 ;;
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dankserver) lan=192.168.0.235 ;;
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*) echo "gpu-exporter: unknown target '$TARGET'" >&2; return 2 ;;
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esac
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mkdir -p "$unit_dir"
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cp scripts/gpu-exporter.service "$unit_dir/gpu-exporter.service"
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dropin="$unit_dir/gpu-exporter.service.d"
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mkdir -p "$dropin"
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printf '[Service]\nEnvironment=GPU_EXPORTER_BINDS=127.0.0.1,%s\n' "$lan" \
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> "$dropin/bind.conf"
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systemctl --user daemon-reload
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systemctl --user enable gpu-exporter.service
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systemctl --user restart gpu-exporter.service
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# The interpreter needs a moment to bind after restart (the same race that
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# once failed a healthy signal-relay deploy).
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for i in $(seq 1 15); do
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curl -fsS -m 5 http://127.0.0.1:9401/metrics >/dev/null && return 0
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sleep 1
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done
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echo "gpu-exporter is not answering on 127.0.0.1:9401/metrics" >&2
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return 1
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}
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copy_loki_config() {
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run_privileged mkdir -p /opt/loki/config
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run_privileged cp shared/loki/loki-config.yaml /opt/loki/config/loki-config.yaml
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@@ -2004,6 +2034,7 @@ deploy_service() {
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tautulli) deploy_tautulli ;;
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alloy) deploy_alloy ;;
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prometheus|grafana|loki|node-exporter|cadvisor|alertmanager) deploy_observability "$service" ;;
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gpu-exporter) deploy_gpu_exporter ;;
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comfyui) deploy_comfyui ;;
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*) deploy_compose_service "$service" ;;
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esac
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Executable
+206
@@ -0,0 +1,206 @@
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#!/usr/bin/env python3
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"""gpu-exporter: unified per-GPU metrics for a mixed AMD/NVIDIA host.
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Emits the `gpu_*` Prometheus families the host-system dashboard graphs:
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gpu_utilization_percent gpu_memory_used_bytes gpu_memory_total_bytes
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gpu_temperature_celsius gpu_power_watts
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each labelled {gpu, vendor, model}. The scrape job adds `host`.
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Two sources, both host-native — no container, no GPU passthrough:
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* AMD (R9700s, the 8060S iGPU, the Raphael display GPU): the amdgpu sysfs tree.
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Utilization comes ONLY from gpu_busy_percent — amd-smi reports gfx_busy_inst
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as N/A on gfx1201 (verified 2026-10-20). VRAM is already bytes, temperature
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is milli-degrees, power is micro-watts. Crucially power1_average is EMPTY on
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the R9700s, so those cards legitimately have no gpu_power_watts line; a
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missing file becomes an ABSENT metric, never a fabricated 0 that a dashboard
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would plot as a real reading.
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* NVIDIA (the RTX 3090 on Dankclaw): one `nvidia-smi --query-gpu` CSV. On
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Dankserver there is an nvidia-smi binary but no NVIDIA GPU, so the command
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fails; that is tolerated and simply yields no NVIDIA series.
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Default mode prints one scrape to stdout and exits (the test harness, and any
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`service ... --oneshot` one-off). `--serve` binds the HTTP endpoint for
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Prometheus; it binds EXPLICITLY (loopback + the host LAN address), never a
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wildcard, matching node-exporter's posture on these boxes.
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"""
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import argparse
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import glob
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import os
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import subprocess
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import sys
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from http.server import BaseHTTPRequestHandler, ThreadingHTTPServer
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FAMILIES = [
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("gpu_utilization_percent", "gauge", "GPU busy time as a percentage of wall time."),
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("gpu_memory_used_bytes", "gauge", "Device memory in use, in bytes."),
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("gpu_memory_total_bytes", "gauge", "Device memory capacity, in bytes."),
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("gpu_temperature_celsius", "gauge", "Package temperature in degrees Celsius."),
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("gpu_power_watts", "gauge", "Board power draw in watts."),
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]
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DEFAULT_NVIDIA_CMD = (
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"nvidia-smi --query-gpu=index,name,utilization.gpu,memory.used,"
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"memory.total,temperature.gpu,power.draw --format=csv,noheader,nounits"
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)
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def _read(path):
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try:
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with open(path) as fh:
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return fh.read().strip()
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except OSError:
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return ""
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def _pci_slot(device_dir):
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uevent = _read(os.path.join(device_dir, "uevent"))
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for line in uevent.splitlines():
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if line.startswith("PCI_SLOT_NAME="):
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return line.split("=", 1)[1]
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return ""
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def _pci_id(device_dir):
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uevent = _read(os.path.join(device_dir, "uevent"))
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for line in uevent.splitlines():
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if line.startswith("PCI_ID="):
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return "amd:" + line.split("=", 1)[1].lower()
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return "amd"
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def collect_amd(sys_dir):
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for card in sorted(glob.glob(os.path.join(sys_dir, "card[0-9]*"))):
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device = os.path.join(card, "device")
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busy = _read(os.path.join(device, "gpu_busy_percent"))
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if busy == "":
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continue # not an amdgpu compute node (e.g. a render node w/o metrics)
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labels = {"gpu": _pci_slot(device) or os.path.basename(card),
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"vendor": "amd", "model": _pci_id(device)}
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yield "gpu_utilization_percent", labels, busy
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for name, leaf in (("gpu_memory_used_bytes", "mem_info_vram_used"),
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("gpu_memory_total_bytes", "mem_info_vram_total")):
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v = _read(os.path.join(device, leaf))
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if v != "":
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yield name, labels, v
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temp = ""
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for hwmon in sorted(glob.glob(os.path.join(device, "hwmon", "hwmon*", "temp1_input"))):
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temp = _read(hwmon)
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if temp != "":
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break
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if temp != "":
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yield "gpu_temperature_celsius", labels, str(int(temp) / 1000.0)
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power = _read(os.path.join(device, "power1_average"))
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if power != "": # empty on the R9700s -> metric absent, not zero
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yield "gpu_power_watts", labels, str(int(power) / 1e6)
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def collect_nvidia(cmd):
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if not cmd:
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return
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try:
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out = subprocess.run(cmd, shell=True, capture_output=True, text=True,
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timeout=10, check=True).stdout
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except (subprocess.SubprocessError, OSError):
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return # no NVIDIA GPU / no driver: tolerate, emit nothing
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for line in out.splitlines():
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parts = [p.strip() for p in line.split(",")]
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if len(parts) < 7:
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continue
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idx, name, util, mused, mtotal, temp, power = parts[:7]
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labels = {"gpu": idx, "vendor": "nvidia", "model": name}
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yield "gpu_utilization_percent", labels, util
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yield "gpu_memory_used_bytes", labels, str(int(float(mused)) * 1048576)
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yield "gpu_memory_total_bytes", labels, str(int(float(mtotal)) * 1048576)
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if temp not in ("", "[N/A]"):
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yield "gpu_temperature_celsius", labels, temp
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if power not in ("", "[N/A]"):
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yield "gpu_power_watts", labels, power
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def collect(sys_dir, nvidia_cmd):
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samples = {}
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for source in (collect_amd(sys_dir), collect_nvidia(nvidia_cmd)):
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for name, labels, value in source:
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try:
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value = str(float(value)) # normalise; drop trailing junk
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||||
except ValueError:
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continue
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samples.setdefault(name, []).append((labels, value))
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return samples
|
||||
|
||||
|
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def _fmt(value):
|
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f = float(value)
|
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if f == int(f) and abs(f) < 1e15:
|
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return str(int(f))
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return repr(f)
|
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|
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def render(samples):
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out = []
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for name, kind, help_text in FAMILIES:
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out.append("# HELP %s %s" % (name, help_text))
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out.append("# TYPE %s %s" % (name, kind))
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for labels, value in sorted(samples.get(name, []), key=lambda x: sorted(x[0].items())):
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lset = ",".join('%s="%s"' % (k, v) for k, v in sorted(labels.items()))
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out.append("%s{%s} %s" % (name, lset, _fmt(value)))
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return "\n".join(out) + "\n"
|
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|
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|
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class Handler(BaseHTTPRequestHandler):
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sys_dir = "/sys/class/drm"
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nvidia_cmd = DEFAULT_NVIDIA_CMD
|
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|
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def do_GET(self): # noqa: N802 (http.server API)
|
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if self.path.split("?")[0] not in ("/metrics", "/"):
|
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self.send_error(404)
|
||||
return
|
||||
body = render(collect(self.sys_dir, self.nvidia_cmd)).encode()
|
||||
self.send_response(200)
|
||||
self.send_header("Content-Type", "text/plain; version=0.0.4")
|
||||
self.send_header("Content-Length", str(len(body)))
|
||||
self.end_headers()
|
||||
self.wfile.write(body)
|
||||
|
||||
def log_message(self, *args):
|
||||
pass
|
||||
|
||||
|
||||
def main(argv):
|
||||
ap = argparse.ArgumentParser(description=__doc__.splitlines()[0])
|
||||
ap.add_argument("--amdgpu-sysfs", default="/sys/class/drm")
|
||||
ap.add_argument("--nvidia-cmd", default=DEFAULT_NVIDIA_CMD)
|
||||
ap.add_argument("--serve", action="store_true", help="serve /metrics instead of one-shot")
|
||||
ap.add_argument("--port", type=int, default=9401)
|
||||
ap.add_argument("--bind", action="append", default=None,
|
||||
help="explicit bind address (repeatable); env GPU_EXPORTER_BINDS "
|
||||
"comma-list if unset. NEVER a wildcard.")
|
||||
args = ap.parse_args(argv)
|
||||
|
||||
if not args.serve:
|
||||
sys.stdout.write(render(collect(args.amdgpu_sysfs, args.nvidia_cmd)))
|
||||
return 0
|
||||
|
||||
binds = args.bind
|
||||
if not binds:
|
||||
env = os.environ.get("GPU_EXPORTER_BINDS", "")
|
||||
binds = [b.strip() for b in env.split(",") if b.strip()] or ["127.0.0.1"]
|
||||
Handler.sys_dir = args.amdgpu_sysfs
|
||||
Handler.nvidia_cmd = args.nvidia_cmd
|
||||
servers = []
|
||||
for b in binds:
|
||||
if b in ("0.0.0.0", "::", "*"):
|
||||
sys.stderr.write("refusing wildcard bind %s\n" % b)
|
||||
return 2
|
||||
servers.append(ThreadingHTTPServer((b, args.port), Handler))
|
||||
sys.stderr.write("gpu-exporter serving :%d on %s\n" % (args.port, ",".join(binds)))
|
||||
servers[0].serve_forever()
|
||||
return 0
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
sys.exit(main(sys.argv[1:]))
|
||||
@@ -0,0 +1,35 @@
|
||||
# Systemd USER unit: gpu-exporter (both Dankclaw and Dankserver).
|
||||
#
|
||||
# Install path: ~/.config/systemd/user/gpu-exporter.service
|
||||
# Installed and enabled by deploy_gpu_exporter in scripts/deploy-remote.sh.
|
||||
#
|
||||
# Per-GPU metrics (utilization / VRAM / temperature / power) for the mixed
|
||||
# AMD + NVIDIA fleet, scraped by Prometheus. Like signal-relay it is a plain
|
||||
# user unit, not a quadlet: it runs python3 straight from the checkout (a pull
|
||||
# updates it with no copy step), a hand-written user unit can be enabled where
|
||||
# the podman v1 generator's units cannot, and with Linger=yes for dank it starts
|
||||
# at boot. It reads the host's own cgroup/drm sysfs and shells to nvidia-smi, so
|
||||
# it must run on the host — a container would need GPU/DRM passthrough for
|
||||
# nothing gained.
|
||||
#
|
||||
# BINDING. The base unit serves loopback only. deploy_gpu_exporter writes a
|
||||
# drop-in adding THIS host's LAN address (the same two-address posture
|
||||
# node-exporter and cadvisor use), so the endpoint is never a wildcard. It is
|
||||
# unauthenticated metrics on the LAN, identical to node-exporter :9100 and
|
||||
# cadvisor :8080 — Prometheus reaches same-host via host.containers.internal and
|
||||
# the Dankserver instance over the LAN from Dankclaw.
|
||||
|
||||
[Unit]
|
||||
Description=GPU metrics exporter (amdgpu sysfs + nvidia-smi)
|
||||
After=network-online.target
|
||||
Wants=network-online.target
|
||||
|
||||
[Service]
|
||||
# Loopback by default; the deploy drop-in appends the host LAN address.
|
||||
Environment=GPU_EXPORTER_BINDS=127.0.0.1
|
||||
ExecStart=/usr/bin/python3 /home/dank/serverAppConfigs/scripts/gpu-exporter.py --serve
|
||||
Restart=always
|
||||
RestartSec=5
|
||||
|
||||
[Install]
|
||||
WantedBy=default.target
|
||||
@@ -293,6 +293,14 @@ for path in "${CHANGED[@]}"; do
|
||||
add_test tests/caddyfile.bats
|
||||
add_test tests/deployment_scoping.bats
|
||||
;;
|
||||
# The GPU exporter is a host process; its seam pins the collector, the
|
||||
# user unit, the deployer function, the planner route, the Prometheus
|
||||
# scrape jobs and the host-system GPU panels — a cross-file contract, so
|
||||
# the whole seam rides on any of its own files.
|
||||
scripts/gpu-exporter.py|scripts/gpu-exporter.service)
|
||||
add_test tests/gpu_exporter.bats
|
||||
add_test tests/deployment_scoping.bats
|
||||
;;
|
||||
dankclaw/udev/*)
|
||||
# Host-level udev rules are applied by manual sudo install + udevadm
|
||||
# trigger, not dispatched as a service; nothing here is bats-testable.
|
||||
|
||||
@@ -2,7 +2,7 @@
|
||||
type: reference
|
||||
title: "Observability on Dankclaw"
|
||||
description: "The observability stack: what runs, how it is deployed, how it is exposed, and what is still unconfigured."
|
||||
tags: [observability, prometheus, grafana, loki, alloy, node-exporter, quadlet, dankclaw]
|
||||
tags: [observability, prometheus, grafana, loki, alloy, node-exporter, gpu-exporter, quadlet, dankclaw]
|
||||
timestamp: 2026-10-20
|
||||
---
|
||||
|
||||
@@ -10,10 +10,10 @@ timestamp: 2026-10-20
|
||||
|
||||
## Summary
|
||||
|
||||
Seven containers and one host-side process: Prometheus (metrics), Grafana
|
||||
Seven containers and two host-side processes: Prometheus (metrics), Grafana
|
||||
(dashboards), Loki (log store), Alloy (log shipper), node-exporter (host
|
||||
metrics), cadvisor (per-container metrics) and Alertmanager (alert delivery), with `signal-relay` on the host
|
||||
carrying every firing group to Signal. All of it is Quadlet-managed,
|
||||
metrics), cadvisor (per-container metrics) and Alertmanager (alert delivery),
|
||||
plus two host `python3` processes — `gpu-exporter` (per-GPU metrics) and `signal-relay` (Signal delivery). The containers are all Quadlet-managed,
|
||||
boot-persistent and loopback-only, deployed by
|
||||
`scripts/deploy-remote.sh` → `deploy_observability`. The metrics half works
|
||||
end to end; the log half is configured, healthy, and carries no data.
|
||||
@@ -35,6 +35,7 @@ that proves it today.
|
||||
| Alloy | `localhost/franksdank/alloy:latest` | `127.0.0.1:12345` | `alloy.container` | [[Alloy]] |
|
||||
| node-exporter | `docker.io/prom/node-exporter:latest` | host netns: `127.0.0.1:9100` + `192.168.0.143:9100` | `node-exporter.container` | [[Node-Exporter]] |
|
||||
| cadvisor | `gcr.io/cadvisor/cadvisor:v0.49.1` | bridge publish `127.0.0.1:8080` + `192.168.0.143:8080` | `cadvisor.container` | — |
|
||||
| GPU exporter | host `python3`, not a container | `127.0.0.1:9401` + host LAN `:9401` | `scripts/gpu-exporter.service` (user unit) | — |
|
||||
| Signal relay | host `python3`, not a container | `192.168.0.143:18093` | `scripts/signal-relay.service` (user unit) | [[Alertmanager]] |
|
||||
|
||||
Every unit lives in `dankclaw/observability/quadlet/`, carries
|
||||
@@ -45,10 +46,11 @@ linger is on for `dank`). `signal-relay.service` reports `enabled` + `active`
|
||||
the same day, and `homepage-status.timer` — the root unit that probes all of
|
||||
these on loopback — is `enabled` + `active` (`deploy-remote.sh:319-321` copies
|
||||
the probe registry `shared/homepage/services.json` to `/srv/homepage`).
|
||||
Dankserver runs two members of this family, node-exporter and cadvisor, as
|
||||
its own units (`dankserver/observability/quadlet/{node-exporter,cadvisor}.container`,
|
||||
Dankserver runs the same family: node-exporter and cadvisor as its own quadlets
|
||||
(`dankserver/observability/quadlet/{node-exporter,cadvisor}.container`,
|
||||
`generated` + `active`; node-exporter binds `127.0.0.1:9100` + `192.168.0.235:9100`,
|
||||
cadvisor publishes `127.0.0.1:8080` + `192.168.0.235:8080`).
|
||||
cadvisor publishes `127.0.0.1:8080` + `192.168.0.235:8080`), plus the host-process
|
||||
`gpu-exporter` (a user unit installed the same way as `signal-relay`).
|
||||
|
||||
## Exposure
|
||||
|
||||
@@ -117,6 +119,18 @@ verify it through the APIs.
|
||||
`container` label. Network and filesystem are NOT exported for these containers
|
||||
(no netns/classid attribution under the host-PID layout), so the dashboard
|
||||
graphs only CPU, memory and OOM and does not fake the rest.
|
||||
* **Per-GPU metrics: the `host-system` GPU panels (added 2026-10-20; live after
|
||||
`deploy.sh <host> --service gpu-exporter`).** `scripts/gpu-exporter.py` is a
|
||||
host-process user unit on BOTH hosts — not a quadlet, because it reads the host's
|
||||
own DRM sysfs and shells to `nvidia-smi`, neither of which a container can do
|
||||
without GPU passthrough. It reads each AMD card's `gpu_busy_percent` /
|
||||
`mem_info_vram_*` / `hwmon temp1_input` and one `nvidia-smi --query-gpu` CSV, and
|
||||
emits unified `gpu_*` families (utilization %, VRAM used/total bytes, temperature
|
||||
°C, power W) labelled `gpu` / `vendor` / `model`, with `host` added by the scrape
|
||||
job. Two laws: **absent means absent, never a zero** — the R9700s expose no sysfs
|
||||
`power1_average`, so they carry no `gpu_power_watts` line at all (only NVIDIA and
|
||||
the Dankclaw 8060S iGPU report power); and it binds loopback + the host LAN, like
|
||||
node-exporter, never the wildcard. The dashboard graphs util/VRAM/VRAM-%/temp/power.
|
||||
* **Logs: fixed in code, awaiting deploy.** The pipeline shipped nothing because
|
||||
a rootless Alloy cannot read the `0640` journal files, and the container-log
|
||||
globs point at a root-storage layout that does not exist here. The fix is built
|
||||
@@ -135,6 +149,7 @@ verify it through the APIs.
|
||||
- `dankclaw/observability/quadlet/{prometheus,alertmanager,grafana,loki,alloy,node-exporter,cadvisor}.container`
|
||||
- `scripts/deploy-remote.sh:219-300` (copiers + relay), `:521-536` (health waits), `:477-486` (grafana env seed)
|
||||
- `scripts/signal-relay.py:26-49`, `scripts/signal-relay.service`
|
||||
- `scripts/gpu-exporter.py`, `scripts/gpu-exporter.service` (per-GPU host exporter)
|
||||
- `shared/prometheus/prometheus.yml`, `shared/prometheus/alertmanager.yml`, `shared/prometheus/rules/llm-fleet.yml`
|
||||
- `shared/grafana/provisioning/`, `shared/loki/loki-config.yaml`, `shared/alloy/config.alloy`
|
||||
- `tests/observability_quadlet.bats` (boot persistence, no wildcard publish, probe addresses, delivery contract)
|
||||
|
||||
@@ -18,6 +18,16 @@
|
||||
"includeAll": true,
|
||||
"multi": true,
|
||||
"current": { "text": "All", "value": "$__all" }
|
||||
},
|
||||
{
|
||||
"name": "gpuhost",
|
||||
"label": "gpu host",
|
||||
"type": "query",
|
||||
"datasource": { "type": "prometheus", "uid": "prometheus" },
|
||||
"query": { "query": "label_values(gpu_utilization_percent, host)", "refId": "A" },
|
||||
"includeAll": true,
|
||||
"multi": true,
|
||||
"current": { "text": "All", "value": "$__all" }
|
||||
}
|
||||
]
|
||||
},
|
||||
@@ -139,6 +149,56 @@
|
||||
{ "expr": "sum by (job,device) (rate(node_network_receive_errs_total{job=~\"$node\"}[5m]))", "legendFormat": "{{job}} {{device}} RX err", "refId": "A" },
|
||||
{ "expr": "sum by (job,device) (rate(node_network_transmit_errs_total{job=~\"$node\"}[5m]))", "legendFormat": "{{job}} {{device}} TX err", "refId": "B" }
|
||||
]
|
||||
},
|
||||
{
|
||||
"id": 13, "type": "timeseries", "title": "GPU busy %",
|
||||
"description": "Per-GPU utilization from gpu-exporter (amdgpu gpu_busy_percent / nvidia-smi). The picker above selects the host; each series is one card.",
|
||||
"gridPos": { "h": 8, "w": 12, "x": 0, "y": 36 },
|
||||
"datasource": { "type": "prometheus", "uid": "prometheus" },
|
||||
"fieldConfig": { "defaults": { "unit": "percent", "min": 0, "max": 100 }, "overrides": [] },
|
||||
"targets": [
|
||||
{ "expr": "gpu_utilization_percent{host=~\"$gpuhost\"}", "legendFormat": "{{host}} {{gpu}} ({{model}})", "refId": "A" }
|
||||
]
|
||||
},
|
||||
{
|
||||
"id": 14, "type": "timeseries", "title": "GPU VRAM used",
|
||||
"description": "Device memory in use. On the R9700s (frank-archon) and the 3090 (frank-zealot) this is the loaded model's footprint.",
|
||||
"gridPos": { "h": 8, "w": 12, "x": 12, "y": 36 },
|
||||
"datasource": { "type": "prometheus", "uid": "prometheus" },
|
||||
"fieldConfig": { "defaults": { "unit": "bytes", "min": 0 }, "overrides": [] },
|
||||
"targets": [
|
||||
{ "expr": "gpu_memory_used_bytes{host=~\"$gpuhost\"}", "legendFormat": "{{host}} {{gpu}} ({{model}})", "refId": "A" }
|
||||
]
|
||||
},
|
||||
{
|
||||
"id": 15, "type": "timeseries", "title": "GPU VRAM used %",
|
||||
"description": "Used / total device memory. Near 100% is the pre-OOM wall.",
|
||||
"gridPos": { "h": 8, "w": 12, "x": 0, "y": 44 },
|
||||
"datasource": { "type": "prometheus", "uid": "prometheus" },
|
||||
"fieldConfig": { "defaults": { "unit": "percent", "min": 0, "max": 100 }, "overrides": [] },
|
||||
"targets": [
|
||||
{ "expr": "100 * gpu_memory_used_bytes{host=~\"$gpuhost\"} / gpu_memory_total_bytes{host=~\"$gpuhost\"}", "legendFormat": "{{host}} {{gpu}} ({{model}})", "refId": "A" }
|
||||
]
|
||||
},
|
||||
{
|
||||
"id": 16, "type": "timeseries", "title": "GPU temperature",
|
||||
"description": "Package temperature. AMD edge temp (hwmon temp1_input); NVIDIA gpu temp.",
|
||||
"gridPos": { "h": 8, "w": 12, "x": 12, "y": 44 },
|
||||
"datasource": { "type": "prometheus", "uid": "prometheus" },
|
||||
"fieldConfig": { "defaults": { "unit": "celsius", "min": 0 }, "overrides": [] },
|
||||
"targets": [
|
||||
{ "expr": "gpu_temperature_celsius{host=~\"$gpuhost\"}", "legendFormat": "{{host}} {{gpu}} ({{model}})", "refId": "A" }
|
||||
]
|
||||
},
|
||||
{
|
||||
"id": 17, "type": "timeseries", "title": "GPU power draw",
|
||||
"description": "Board power draw. Emitted only where readable: NVIDIA and the Dankclaw iGPU. The R9700s have no sysfs power sensor, so they are simply absent here — never a fabricated 0.",
|
||||
"gridPos": { "h": 8, "w": 12, "x": 0, "y": 52 },
|
||||
"datasource": { "type": "prometheus", "uid": "prometheus" },
|
||||
"fieldConfig": { "defaults": { "unit": "watt", "min": 0 }, "overrides": [] },
|
||||
"targets": [
|
||||
{ "expr": "gpu_power_watts{host=~\"$gpuhost\"}", "legendFormat": "{{host}} {{gpu}} ({{model}})", "refId": "A" }
|
||||
]
|
||||
}
|
||||
]
|
||||
}
|
||||
|
||||
@@ -191,3 +191,25 @@ scrape_configs:
|
||||
action: keep
|
||||
- regex: 'id|name|image|container_label.*|machine_id|boot_id'
|
||||
action: labeldrop
|
||||
|
||||
# Per-GPU metrics (gpu_utilization_percent / gpu_memory_used_bytes /
|
||||
# gpu_memory_total_bytes / gpu_temperature_celsius / gpu_power_watts) from the
|
||||
# host-process gpu-exporter (scripts/gpu-exporter.py). One job per host, same
|
||||
# reach rules as node/cadvisor: Dankclaw is scraped at the podman gateway
|
||||
# because the netavark hairpin quirk makes Prometheus fail to dial its own
|
||||
# host LAN IP; Dankserver is plain LAN. The gpu label (PCI BDF on AMD, index on
|
||||
# NVIDIA) + vendor/model come from the exporter, so the GPU row on the
|
||||
# host-system dashboard filters by host. Power is emitted only where readable
|
||||
# (NVIDIA + the Dankclaw iGPU); the R9700s have no sysfs power, so they simply
|
||||
# have no gpu_power_watts series — no fabricated zero.
|
||||
- job_name: "gpu-dankclaw"
|
||||
static_configs:
|
||||
- targets: ["host.containers.internal:9401"]
|
||||
labels:
|
||||
host: dankclaw
|
||||
|
||||
- job_name: "gpu-dankserver"
|
||||
static_configs:
|
||||
- targets: ["192.168.0.235:9401"]
|
||||
labels:
|
||||
host: dankserver
|
||||
|
||||
Executable
+197
@@ -0,0 +1,197 @@
|
||||
#!/usr/bin/env bats
|
||||
# Seam: the GPU metrics exporter's black-box contract.
|
||||
#
|
||||
# The exporter reads amdgpu sysfs (one card per /sys/class/drm/cardN that has a
|
||||
# device/gpu_busy_percent file) and, on the box that has a working NVIDIA stack,
|
||||
# one `nvidia-smi --query-gpu` CSV, and emits the unified `gpu_*` Prometheus
|
||||
# families the host-system dashboard graphs. Both sources are injectable so the
|
||||
# whole thing is testable with fixtures on a GPU-less dev box.
|
||||
#
|
||||
# Only the inputs a consumer sees are pinned: the metric families, their label
|
||||
# set, and that absent hardware yields ABSENT series (never a fabricated 0 — a
|
||||
# wrong number on a dashboard gets believed). The R9700s expose no sysfs
|
||||
# power1_average, so those cards legitimately carry no gpu_power_watts line.
|
||||
|
||||
load helpers
|
||||
|
||||
EXPORTER="$REPO_ROOT/scripts/gpu-exporter.py"
|
||||
|
||||
# Build a fixture amdgpu sysfs tree. $BATS_TEST_TMPDIR/sys
|
||||
mk_amd() { # gpu busy vram_used vram_total power_uw_or_blank temp_mc
|
||||
local card=$1 busy=$2 used=$3 total=$4 power=$5 temp=$6
|
||||
local d="$SYS/card$card/device"
|
||||
mkdir -p "$d/hwmon/hwmon9"
|
||||
printf '%s\n' "$busy" > "$d/gpu_busy_percent"
|
||||
printf '%s\n' "$used" > "$d/mem_info_vram_used"
|
||||
printf '%s\n' "$total" > "$d/mem_info_vram_total"
|
||||
printf '%s\n' "$power" > "$d/power1_average" # blank => absent on R9700
|
||||
[ -n "$temp" ] && printf '%s\n' "$temp" > "$d/hwmon/hwmon9/temp1_input"
|
||||
printf 'DRIVER=amdgpu\nPCI_ID=1002:7551\nPCI_SLOT_NAME=0000:03:00.0\n' > "$d/uevent"
|
||||
}
|
||||
|
||||
setup() {
|
||||
SYS="$BATS_TEST_TMPDIR/sys"
|
||||
mkdir -p "$SYS"
|
||||
}
|
||||
|
||||
@test "exporter exists and compiles" {
|
||||
[ -f "$EXPORTER" ]
|
||||
python3 -m py_compile "$EXPORTER"
|
||||
}
|
||||
|
||||
@test "amd card with full sysfs yields util/vram/temp/power with the right labels and units" {
|
||||
mk_amd 1 42 1073741824 34359738368 250000000 71000 # 250 W, 71 C
|
||||
run python3 "$EXPORTER" --amdgpu-sysfs "$SYS" --nvidia-cmd false
|
||||
[ "$status" -eq 0 ] || { echo "$output"; return 1; }
|
||||
# util is a raw percent, VRAM verbatim bytes, temp milli->C, power microW->W.
|
||||
echo "$output" | grep -Eq 'gpu_utilization_percent\{[^}]*vendor="amd"[^}]*\} 42$' || { echo "$output"; return 1; }
|
||||
echo "$output" | grep -Eq 'gpu_memory_used_bytes\{[^}]*\} 1073741824$' || { echo "$output"; return 1; }
|
||||
echo "$output" | grep -Eq 'gpu_memory_total_bytes\{[^}]*\} 34359738368$' || { echo "$output"; return 1; }
|
||||
echo "$output" | grep -Eq 'gpu_temperature_celsius\{[^}]*\} 71$' || { echo "$output"; return 1; }
|
||||
echo "$output" | grep -Eq 'gpu_power_watts\{[^}]*\} 250$' || { echo "$output"; return 1; }
|
||||
# identity labels: the PCI slot is a stable unique id, vendor marks the family.
|
||||
echo "$output" | grep -Eq 'gpu_utilization_percent\{.*gpu="0000:03:00\.0"' || { echo "$output"; return 1; }
|
||||
}
|
||||
|
||||
@test "card with an empty power file and no hwmon yields util/vram but omits power and temp" {
|
||||
mk_amd 1 99 34108338176 34208743424 "" "" # the R9700 shape
|
||||
run python3 "$EXPORTER" --amdgpu-sysfs "$SYS" --nvidia-cmd false
|
||||
[ "$status" -eq 0 ] || { echo "$output"; return 1; }
|
||||
echo "$output" | grep -Eq 'gpu_utilization_percent\{[^}]*\} 99$' || { echo "$output"; return 1; }
|
||||
echo "$output" | grep -Eq 'gpu_memory_used_bytes\{[^}]*\} 34108338176$'
|
||||
# Absent means ABSENT, not a zero the dashboard would plot as a real reading.
|
||||
! echo "$output" | grep -Eq '^gpu_power_watts\{' || { echo "fabricated power line: $output"; return 1; }
|
||||
! echo "$output" | grep -Eq '^gpu_temperature_celsius\{' || { echo "fabricated temp line: $output"; return 1; }
|
||||
}
|
||||
|
||||
@test "nvidia csv yields util/vram/temp/power tagged vendor=nvidia" {
|
||||
nvidia="$BATS_TEST_TMPDIR/nvidia-smi"
|
||||
cat > "$nvidia" <<'STUB'
|
||||
echo '0, NVIDIA GeForce RTX 3090, 93, 23004, 24576, 76, 397.40'
|
||||
STUB
|
||||
chmod +x "$nvidia"
|
||||
run python3 "$EXPORTER" --amdgpu-sysfs "$SYS" --nvidia-cmd "$nvidia"
|
||||
[ "$status" -eq 0 ] || { echo "$output"; return 1; }
|
||||
echo "$output" | grep -Eq 'gpu_utilization_percent\{[^}]*vendor="nvidia"[^}]*\} 93$' || { echo "$output"; return 1; }
|
||||
# memory.used MiB -> bytes (23004 * 1048576)
|
||||
echo "$output" | grep -Eq 'gpu_memory_used_bytes\{[^}]*vendor="nvidia"[^}]*\} 24121442304$' || { echo "$output"; return 1; }
|
||||
echo "$output" | grep -Eq 'gpu_temperature_celsius\{[^}]*vendor="nvidia"[^}]*\} 76$'
|
||||
echo "$output" | grep -Eq 'gpu_power_watts\{[^}]*vendor="nvidia"[^}]*\} 397\.4$'
|
||||
echo "$output" | grep -Eq 'model="NVIDIA GeForce RTX 3090"'
|
||||
}
|
||||
|
||||
@test "a failing nvidia command is tolerated: amd still emits and exit is 0" {
|
||||
mk_amd 1 50 1000000 2000000 "" 40000
|
||||
failing="$BATS_TEST_TMPDIR/nvidia-fail"
|
||||
printf '#!/bin/sh\nexit 1\n' > "$failing"; chmod +x "$failing"
|
||||
run python3 "$EXPORTER" --amdgpu-sysfs "$SYS" --nvidia-cmd "$failing"
|
||||
[ "$status" -eq 0 ] || { echo "$output"; return 1; }
|
||||
echo "$output" | grep -Eq 'gpu_utilization_percent\{[^}]*vendor="amd"[^}]*\} 50$'
|
||||
! echo "$output" | grep -q 'vendor="nvidia"'
|
||||
}
|
||||
|
||||
@test "no GPUs at all yields only HELP/TYPE headers and exits 0" {
|
||||
run python3 "$EXPORTER" --amdgpu-sysfs "$SYS" --nvidia-cmd false
|
||||
[ "$status" -eq 0 ] || { echo "$output"; return 1; }
|
||||
# families are declared even when empty, so the dashboard/queries stay valid.
|
||||
echo "$output" | grep -q '# TYPE gpu_utilization_percent gauge'
|
||||
echo "$output" | grep -q '# TYPE gpu_memory_used_bytes gauge'
|
||||
! echo "$output" | grep -Eq '^gpu_utilization_percent\{'
|
||||
}
|
||||
|
||||
@test "output is valid Prometheus text" {
|
||||
mk_amd 1 42 1000 2000 "" 50000
|
||||
run python3 "$EXPORTER" --amdgpu-sysfs "$SYS" --nvidia-cmd false
|
||||
[ "$status" -eq 0 ]
|
||||
# every non-comment line is "<name>{labels} value" or "<name> value"
|
||||
printf '%s\n' "$output" | python3 -c '
|
||||
import sys, re
|
||||
pat = re.compile(r"^[a-z_]+(\{[^}]*\})? [-+0-9.eE+]+$")
|
||||
for i, l in enumerate(sys.stdin):
|
||||
l = l.rstrip("\n")
|
||||
if not l or l.startswith("#"):
|
||||
continue
|
||||
assert pat.match(l), "malformed line %d: %r" % (i, l)
|
||||
print("prometheus text ok")
|
||||
'
|
||||
}
|
||||
|
||||
# ---- deployment + wiring contracts -------------------------------------
|
||||
# The exporter is a HOST-PROCESS user unit (not a quadlet): it must read the
|
||||
# host's own DRM sysfs and shell to nvidia-smi, which a container could not do
|
||||
# without GPU passthrough. These tests pin the cross-file wiring a reader
|
||||
# cannot eyeball — a lone change on one side leaves the metric silently absent.
|
||||
|
||||
@test "the base unit runs the exporter from the checkout and never binds a wildcard" {
|
||||
local u="$REPO_ROOT/scripts/gpu-exporter.service"
|
||||
[ -f "$u" ]
|
||||
grep -q '^ExecStart=/usr/bin/python3 /home/dank/serverAppConfigs/scripts/gpu-exporter.py --serve$' "$u" \
|
||||
|| { echo "unit does not run the exporter --serve from the checkout"; return 1; }
|
||||
grep -q '^Restart=always$' "$u"
|
||||
grep -q '^WantedBy=default.target$' "$u"
|
||||
# Base unit binds loopback only; the per-host LAN address is added by a
|
||||
# deploy drop-in, so a checked-in unit is never a wildcard.
|
||||
grep -q '^Environment=GPU_EXPORTER_BINDS=127.0.0.1$' "$u"
|
||||
! grep -qE '0\.0\.0\.0' "$u"
|
||||
}
|
||||
|
||||
@test "the deployer installs, drops in the LAN bind, and health-gates gpu-exporter" {
|
||||
local handler="$REPO_ROOT/scripts/deploy-remote.sh"
|
||||
grep -q '^deploy_gpu_exporter() {' "$handler"
|
||||
# Per-host LAN from $TARGET (never a hardcoded host, never a wildcard).
|
||||
grep -q 'dankclaw) lan=192.168.0.143' "$handler"
|
||||
grep -q 'dankserver) lan=192.168.0.235' "$handler"
|
||||
# Drop-in binds loopback + this host's LAN as one comma list.
|
||||
grep -q "GPU_EXPORTER_BINDS=127.0.0.1,%s" "$handler"
|
||||
grep -q 'systemctl --user enable gpu-exporter.service' "$handler"
|
||||
grep -q 'systemctl --user restart gpu-exporter.service' "$handler"
|
||||
# Health gate waits on the loopback metrics endpoint.
|
||||
grep -q 'http://127.0.0.1:9401/metrics' "$handler"
|
||||
# Dispatched from the central case.
|
||||
grep -q 'gpu-exporter) deploy_gpu_exporter ;;' "$handler"
|
||||
# Allowlisted on BOTH hosts.
|
||||
grep -q 'dankclaw:gpu-exporter' "$handler"
|
||||
grep -q 'dankserver:gpu-exporter' "$handler"
|
||||
}
|
||||
|
||||
@test "the planner selects gpu-exporter for its files on each target" {
|
||||
local t f
|
||||
for t in dankclaw dankserver; do
|
||||
for f in scripts/gpu-exporter.py scripts/gpu-exporter.service; do
|
||||
run python3 "$REPO_ROOT/scripts/deploy-plan.py" --target "$t" --paths "$f"
|
||||
[ "$status" -eq 0 ]
|
||||
[ "$output" = "gpu-exporter" ] || { echo "$t/$f -> '$output'"; return 1; }
|
||||
done
|
||||
done
|
||||
}
|
||||
|
||||
@test "Prometheus scrapes gpu-exporter where node/cadvisor are reachable on each host" {
|
||||
# Cross-file contract, same posture as node-exporter: the local instance is
|
||||
# reached via the podman gateway (this Prometheus is a bridge container and
|
||||
# a host-process bind is refused at the host LAN IP); the Dankserver
|
||||
# instance is a different machine, so plain LAN routing reaches it. If either
|
||||
# address drifts from the exporter's bind, GPU panels go blank with no error.
|
||||
local cfg="$REPO_ROOT/shared/prometheus/prometheus.yml"
|
||||
grep -q 'job_name: "gpu-dankclaw"' "$cfg" || { echo "no gpu-dankclaw job"; return 1; }
|
||||
grep -q 'job_name: "gpu-dankserver"' "$cfg" || { echo "no gpu-dankserver job"; return 1; }
|
||||
grep -q '"host.containers.internal:9401"' "$cfg" \
|
||||
|| { echo "gpu-dankclaw does not scrape the podman gateway"; return 1; }
|
||||
grep -q '"192.168.0.235:9401"' "$cfg" \
|
||||
|| { echo "gpu-dankserver does not scrape the LAN address"; return 1; }
|
||||
# A vhost target would be red forever (Prometheus cannot solve Anubis).
|
||||
! grep -qE '"[^"]*franksdank[^"]*:9401"' "$cfg"
|
||||
}
|
||||
|
||||
@test "the host-system dashboard graphs the gpu_* families the exporter emits" {
|
||||
local dash="$REPO_ROOT/shared/grafana/provisioning/dashboards/host-system.json"
|
||||
[ -f "$dash" ]
|
||||
python3 -c "
|
||||
import json
|
||||
d = json.load(open('$dash'))
|
||||
exprs = [t['expr'] for p in d['panels'] for t in p.get('targets', [])]
|
||||
for want in ('gpu_utilization_percent', 'gpu_memory_used_bytes',
|
||||
'gpu_temperature_celsius', 'gpu_power_watts'):
|
||||
assert any(want in e for e in exprs), ('missing', want, exprs)
|
||||
print('gpu dashboard panels ok')
|
||||
"
|
||||
}
|
||||
Reference in New Issue
Block a user