feat(observability): per-GPU metrics for the mixed AMD/NVIDIA fleet

Add a host-process GPU exporter, scrape it on both servers, and graph it
on the host-system dashboard. The fleet has four GPUs across three vendors
of interest (2x R9700 on Dankserver, the 8060S iGPU + RTX 3090 on Dankclaw)
and nothing exposed them until now.

scripts/gpu-exporter.py reads each AMD card's amdgpu sysfs
(gpu_busy_percent / mem_info_vram_* / hwmon temp1_input / power1_average)
plus one nvidia-smi --query-gpu CSV, and emits unified gpu_* Prometheus
families (utilization_percent, memory_used/total_bytes, temperature_celsius,
power_watts) labelled gpu/vendor/model. Absent hardware yields ABSENT series,
never a fabricated 0: the R9700s expose no sysfs power, so they simply carry
no gpu_power_watts line. Both sources are injectable, so the seam runs on a
GPU-less dev box; live-verified on Dankserver's real sysfs.

It runs as a plain user unit (not a quadlet): it must read the host's own DRM
sysfs and shell to nvidia-smi, which a container cannot do without GPU
passthrough. Same posture as signal-relay. The base unit binds loopback; the
deploy drop-in appends the host LAN address, never a wildcard (matching
node-exporter/cadvisor). deploy_gpu_exporter installs/enables/health-gates it
on both hosts and is wired into the planner (both targets), the test-changed
router, and two Prometheus scrape jobs using the node/cadvisor reach rules
(gateway on Dankclaw, LAN on Dankserver).

scripts/deploy-plan.py

@@ -40,6 +40,7 @@ SERVICE_ORDER = (
     "alloy",
     "node-exporter",
     "cadvisor",
+    "gpu-exporter",
     "alertmanager",
     "authentik-postgres",
     "authentik-server",
@@ -94,6 +95,7 @@ DANKCLAW_SERVICES = {
     "alloy",
     "node-exporter",
     "cadvisor",
+    "gpu-exporter",
     "alertmanager",
     "authentik-postgres",
     "authentik-server",
@@ -127,6 +129,7 @@ DANKSERVER_SERVICES = {
     "frank-archon",
     "node-exporter",
     "cadvisor",
+    "gpu-exporter",
 }
 
 # FrankBook-Pro runs the *arr stack + qBittorrent inside a podman machine on
@@ -452,6 +455,12 @@ def services_for_path(path: str, target: str) -> set[str]:
             # change to it redeploying alertmanager is the only path that
             # reaches it on the host.
             _add(services, "alertmanager")
+        if name in {"gpu-exporter.py", "gpu-exporter.service"}:
+            # The host-process GPU exporter is installed directly by the
+            # gpu-exporter deploy on BOTH hosts, so its script and unit select
+            # that service (target_services then keeps it only on the host being
+            # planned). Editing the collector restarts the running exporter.
+            _add(services, "gpu-exporter")
         if name in {"frank-zealot.env", "frank-zealot.service", "serve-frank-zealot.sh"}:
             # llama.cpp frank-zealot (2026-09-16) keeps its unit, env and serve
             # files here; each one selects frank-zealot only. The ik_llama.cpp

scripts/deploy-remote.sh

@@ -86,7 +86,7 @@ service_is_allowed() {
         dankclaw:open-webui|dankclaw:gitea-postgres|dankclaw:gitea-server|\
         dankclaw:comfyui|dankclaw:hermes|\
         dankclaw:hermes-dashboard|dankclaw:hermes-webui|dankclaw:prometheus|dankclaw:grafana|\
-        dankclaw:loki|dankclaw:alloy|dankclaw:node-exporter|dankclaw:cadvisor|dankclaw:alertmanager|\
+        dankclaw:loki|dankclaw:alloy|dankclaw:node-exporter|dankclaw:cadvisor|dankclaw:gpu-exporter|dankclaw:alertmanager|\
         dankclaw:authentik-postgres|dankclaw:authentik-server|\
         dankclaw:authentik-worker|dankclaw:authentik-outpost|dankclaw:authentik-outpost-ldap|dankclaw:anubis|\
         dankclaw:caddy|dankclaw:homepage|dankclaw:seerr|dankclaw:marreta|\
@@ -97,7 +97,7 @@ service_is_allowed() {
         dankserver:copyparty|dankserver:jellyfin|dankserver:calibre-web|dankserver:calibre-server|dankserver:plex|dankserver:tautulli|\
         dankserver:prowlarr|dankserver:qbittorrent|dankserver:radarr|\
         dankserver:sonarr|dankserver:lidarr|dankserver:readarr|\
-        dankserver:frank-archon|dankserver:node-exporter|dankserver:cadvisor|\
+        dankserver:frank-archon|dankserver:node-exporter|dankserver:cadvisor|dankserver:gpu-exporter|\
         frankbook-pro:gluetun|frankbook-pro:qbittorrent|frankbook-pro:prowlarr|\
         frankbook-pro:radarr|frankbook-pro:sonarr|frankbook-pro:lidarr|\
         frankbook-pro:readarr)
@@ -275,6 +275,36 @@ install_signal_relay() {
     return 1
 }
 
+# Host-process GPU metrics exporter (amdgpu sysfs + nvidia-smi). Not a quadlet:
+# it runs python3 from the checkout on the host so it can read the DRM/cgroup
+# sysfs and shell out to nvidia-smi. Same two-address bind posture as
+# node-exporter/cadvisor (loopback + this host's LAN), so it is never a wildcard.
+deploy_gpu_exporter() {
+    local unit_dir="$HOME/.config/systemd/user" lan dropin i
+    case "$TARGET" in
+        dankclaw) lan=192.168.0.143 ;;
+        dankserver) lan=192.168.0.235 ;;
+        *) echo "gpu-exporter: unknown target '$TARGET'" >&2; return 2 ;;
+    esac
+    mkdir -p "$unit_dir"
+    cp scripts/gpu-exporter.service "$unit_dir/gpu-exporter.service"
+    dropin="$unit_dir/gpu-exporter.service.d"
+    mkdir -p "$dropin"
+    printf '[Service]\nEnvironment=GPU_EXPORTER_BINDS=127.0.0.1,%s\n' "$lan" \
+        > "$dropin/bind.conf"
+    systemctl --user daemon-reload
+    systemctl --user enable gpu-exporter.service
+    systemctl --user restart gpu-exporter.service
+    # The interpreter needs a moment to bind after restart (the same race that
+    # once failed a healthy signal-relay deploy).
+    for i in $(seq 1 15); do
+        curl -fsS -m 5 http://127.0.0.1:9401/metrics >/dev/null && return 0
+        sleep 1
+    done
+    echo "gpu-exporter is not answering on 127.0.0.1:9401/metrics" >&2
+    return 1
+}
+
 copy_loki_config() {
     run_privileged mkdir -p /opt/loki/config
     run_privileged cp shared/loki/loki-config.yaml /opt/loki/config/loki-config.yaml
@@ -2004,6 +2034,7 @@ deploy_service() {
         tautulli) deploy_tautulli ;;
         alloy) deploy_alloy ;;
         prometheus|grafana|loki|node-exporter|cadvisor|alertmanager) deploy_observability "$service" ;;
+        gpu-exporter) deploy_gpu_exporter ;;
         comfyui) deploy_comfyui ;;
         *) deploy_compose_service "$service" ;;
     esac

scripts/gpu-exporter.py

@@ -0,0 +1,206 @@
+#!/usr/bin/env python3
+"""gpu-exporter: unified per-GPU metrics for a mixed AMD/NVIDIA host.
+
+Emits the `gpu_*` Prometheus families the host-system dashboard graphs:
+
+    gpu_utilization_percent  gpu_memory_used_bytes  gpu_memory_total_bytes
+    gpu_temperature_celsius  gpu_power_watts
+
+each labelled {gpu, vendor, model}. The scrape job adds `host`.
+
+Two sources, both host-native — no container, no GPU passthrough:
+
+  * AMD (R9700s, the 8060S iGPU, the Raphael display GPU): the amdgpu sysfs tree.
+    Utilization comes ONLY from gpu_busy_percent — amd-smi reports gfx_busy_inst
+    as N/A on gfx1201 (verified 2026-10-20). VRAM is already bytes, temperature
+    is milli-degrees, power is micro-watts. Crucially power1_average is EMPTY on
+    the R9700s, so those cards legitimately have no gpu_power_watts line; a
+    missing file becomes an ABSENT metric, never a fabricated 0 that a dashboard
+    would plot as a real reading.
+
+  * NVIDIA (the RTX 3090 on Dankclaw): one `nvidia-smi --query-gpu` CSV. On
+    Dankserver there is an nvidia-smi binary but no NVIDIA GPU, so the command
+    fails; that is tolerated and simply yields no NVIDIA series.
+
+Default mode prints one scrape to stdout and exits (the test harness, and any
+`service ... --oneshot` one-off). `--serve` binds the HTTP endpoint for
+Prometheus; it binds EXPLICITLY (loopback + the host LAN address), never a
+wildcard, matching node-exporter's posture on these boxes.
+"""
+import argparse
+import glob
+import os
+import subprocess
+import sys
+from http.server import BaseHTTPRequestHandler, ThreadingHTTPServer
+
+FAMILIES = [
+    ("gpu_utilization_percent", "gauge", "GPU busy time as a percentage of wall time."),
+    ("gpu_memory_used_bytes", "gauge", "Device memory in use, in bytes."),
+    ("gpu_memory_total_bytes", "gauge", "Device memory capacity, in bytes."),
+    ("gpu_temperature_celsius", "gauge", "Package temperature in degrees Celsius."),
+    ("gpu_power_watts", "gauge", "Board power draw in watts."),
+]
+
+DEFAULT_NVIDIA_CMD = (
+    "nvidia-smi --query-gpu=index,name,utilization.gpu,memory.used,"
+    "memory.total,temperature.gpu,power.draw --format=csv,noheader,nounits"
+)
+
+
+def _read(path):
+    try:
+        with open(path) as fh:
+            return fh.read().strip()
+    except OSError:
+        return ""
+
+
+def _pci_slot(device_dir):
+    uevent = _read(os.path.join(device_dir, "uevent"))
+    for line in uevent.splitlines():
+        if line.startswith("PCI_SLOT_NAME="):
+            return line.split("=", 1)[1]
+    return ""
+
+
+def _pci_id(device_dir):
+    uevent = _read(os.path.join(device_dir, "uevent"))
+    for line in uevent.splitlines():
+        if line.startswith("PCI_ID="):
+            return "amd:" + line.split("=", 1)[1].lower()
+    return "amd"
+
+
+def collect_amd(sys_dir):
+    for card in sorted(glob.glob(os.path.join(sys_dir, "card[0-9]*"))):
+        device = os.path.join(card, "device")
+        busy = _read(os.path.join(device, "gpu_busy_percent"))
+        if busy == "":
+            continue  # not an amdgpu compute node (e.g. a render node w/o metrics)
+        labels = {"gpu": _pci_slot(device) or os.path.basename(card),
+                  "vendor": "amd", "model": _pci_id(device)}
+        yield "gpu_utilization_percent", labels, busy
+        for name, leaf in (("gpu_memory_used_bytes", "mem_info_vram_used"),
+                           ("gpu_memory_total_bytes", "mem_info_vram_total")):
+            v = _read(os.path.join(device, leaf))
+            if v != "":
+                yield name, labels, v
+        temp = ""
+        for hwmon in sorted(glob.glob(os.path.join(device, "hwmon", "hwmon*", "temp1_input"))):
+            temp = _read(hwmon)
+            if temp != "":
+                break
+        if temp != "":
+            yield "gpu_temperature_celsius", labels, str(int(temp) / 1000.0)
+        power = _read(os.path.join(device, "power1_average"))
+        if power != "":  # empty on the R9700s -> metric absent, not zero
+            yield "gpu_power_watts", labels, str(int(power) / 1e6)
+
+
+def collect_nvidia(cmd):
+    if not cmd:
+        return
+    try:
+        out = subprocess.run(cmd, shell=True, capture_output=True, text=True,
+                             timeout=10, check=True).stdout
+    except (subprocess.SubprocessError, OSError):
+        return  # no NVIDIA GPU / no driver: tolerate, emit nothing
+    for line in out.splitlines():
+        parts = [p.strip() for p in line.split(",")]
+        if len(parts) < 7:
+            continue
+        idx, name, util, mused, mtotal, temp, power = parts[:7]
+        labels = {"gpu": idx, "vendor": "nvidia", "model": name}
+        yield "gpu_utilization_percent", labels, util
+        yield "gpu_memory_used_bytes", labels, str(int(float(mused)) * 1048576)
+        yield "gpu_memory_total_bytes", labels, str(int(float(mtotal)) * 1048576)
+        if temp not in ("", "[N/A]"):
+            yield "gpu_temperature_celsius", labels, temp
+        if power not in ("", "[N/A]"):
+            yield "gpu_power_watts", labels, power
+
+
+def collect(sys_dir, nvidia_cmd):
+    samples = {}
+    for source in (collect_amd(sys_dir), collect_nvidia(nvidia_cmd)):
+        for name, labels, value in source:
+            try:
+                value = str(float(value))  # normalise; drop trailing junk
+            except ValueError:
+                continue
+            samples.setdefault(name, []).append((labels, value))
+    return samples
+
+
+def _fmt(value):
+    f = float(value)
+    if f == int(f) and abs(f) < 1e15:
+        return str(int(f))
+    return repr(f)
+
+
+def render(samples):
+    out = []
+    for name, kind, help_text in FAMILIES:
+        out.append("# HELP %s %s" % (name, help_text))
+        out.append("# TYPE %s %s" % (name, kind))
+        for labels, value in sorted(samples.get(name, []), key=lambda x: sorted(x[0].items())):
+            lset = ",".join('%s="%s"' % (k, v) for k, v in sorted(labels.items()))
+            out.append("%s{%s} %s" % (name, lset, _fmt(value)))
+    return "\n".join(out) + "\n"
+
+
+class Handler(BaseHTTPRequestHandler):
+    sys_dir = "/sys/class/drm"
+    nvidia_cmd = DEFAULT_NVIDIA_CMD
+
+    def do_GET(self):  # noqa: N802 (http.server API)
+        if self.path.split("?")[0] not in ("/metrics", "/"):
+            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:]))

scripts/gpu-exporter.service

@@ -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

scripts/test-changed.sh

@@ -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.

serverAppConfigs-docs/Infrastructure/Observability.md

@@ -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)

shared/grafana/provisioning/dashboards/host-system.json

@@ -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" }
+      ]
     }
   ]
 }

shared/prometheus/prometheus.yml

@@ -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

tests/gpu_exporter.bats

@@ -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')
+"
+}