Census: all 5 provisioned dashboards, 56 targets, every expression
re-evaluated against the live Prometheus/Loki with template vars expanded
(queries must run from the host: both APIs bind 127.0.0.1; from the dev box
that is connection-refused, which is NOT a dashboard defect).
- host-system 'Load 5m / core' was STRUCTURALLY EMPTY: bare '/' drops
non-matching pairs and the right side collapses to {job} while the left
carries {job,instance} -> 0 series forever. Fixed with / on(job); proven
live (2 series).
- containers 'Memory vs limit (%)' was STRUCTURALLY EMPTY: every
container_spec_memory_limit_bytes on this fleet is 0 (no cgroup limits),
so the '> 0' filter can never match. Rewritten to share-of-host-total via
label_replace join of the node exporter's MemTotal by host (the parens
form is a PromQL parse error: nothing may follow group_left); 62 series
live. Panel unit percentunit kept -> expression returns a fraction.
- llm-fleet 'Firing fleet alerts' is legitimately empty when healthy
(ALERTS carries only firing/pending series); description now says so,
per the Stale Signal rule that 0-series-on-ALERTS is not a defect.
logs-overview and observability: all targets already returning data.
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).
llm-fleet.json already owns LLM capacity+spec-decode. These three cover the
domains that had NO dashboard:
- host-system: node_exporter CPU/Load/Mem/Disk/Net/Uptime/FS/FDs for both
Dankclaw and Dankserver (templated by job node-dankclaw|node-dankserver)
- logs-overview: Loki volume + per-container error rate + a sample log panel;
container is parsed from the JSON line at query time (journal streams have
no container_name stream label)
- observability: the stack's own health - Prometheus target up/down + scrape
interval drift + samples/s + TSDB, Loki ingest/discard, Grafana CPU/mem.
Panel queries verified live against Prometheus/Loki; provisioned dashboards
confirmed via /api/search. Alertmanager is running but NOT scraped by
Prometheus - noted in the dashboard, no empty panels built on it.
Frank