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