/metrics?model=Qwen3.6 forces the router to attempt loading Qwen3.6 every
90s scrape cycle, triggering a CUDA OOM error since VRAM is already consumed
by the resident Llama3+Phi3.5 models. This produces real GPU power spikes
(~110W load-attempt), not a benign counter read like the Llama3/Phi3.5 jobs.
nvidia_gpu_exporter (:9835) already provides GPU power/VRAM/utilization at
zero wake cost. No Grafana dashboard panel references Qwen3.6 model-specific
llama-server metrics. Ryan approved full removal.
Job is commented out (not deleted) for easy revert if Qwen3.6 is ever
re-added as a resident model. Llama3/Phi3.5 scrape jobs untouched.
Each /metrics?model=<id> request on the llama.cpp router wakes the GPU
sub-server to P2 (~110W). At 15s with two active jobs (llama3 + phi35),
combined scrape frequency (~7-8s effective) keeps the GPU continuously at
P2 despite zero real inference requests.
At 90s: each scrape wakes GPU for ~5-10s then it drops to P8 (~20W) for
~80s. Verified via iptables block test on 2026-08-13 (t_e7d547ea):
Before block: 110-115W P2 continuously
After block: 19-21W P8 consistently
After unblock: returned to 110W P2 within seconds
qwen3 interval also set to 90s (model not loaded so moot, but consistent).
Ref: t_e7d547ea
Port 8000 (gemma-2-27b-it-GGUF) is dead after the day2 router cutover on
2026-08-12. Production inference now runs through llama-server-router on
port 8002.
The router exposes per-model Prometheus metrics via /metrics?model=<id>.
Since a single /metrics request without ?model returns HTTP 400, replaced
the single stale job with three per-model jobs — one per model registered
in the router per /v1/models:
- Qwen3.6-35B-A3B-UD-Q4_K_S (currently unloaded but registered)
- Meta-Llama-3.1-8B-Instruct-Q4_K_M (loaded)
- Phi-3.5-mini-instruct-Q8_0 (loaded)
Static 'model' label carries the canonical llama.cpp model id (not alias).
Added 'endpoint: astro-orbiter-router' to identify the scrape origin.
Removed dead :8000 target entirely.
- Prometheus scrape configs for node/gpu/llama-server exporters on
astro-orbiter now declared in cluster/applications/monitoring/values.yaml
(additionalScrapeConfigs), applied via ArgoCD sync instead of an
imperative kubectl secret patch from the Ansible role.
- Grafana dashboard for astro-orbiter LLM inference added as a ConfigMap
in cluster/applications/monitoring/dashboards.yaml (grafana_dashboard=1
sidecar label), replacing the role's ad-hoc kubectl apply of a rendered
Jinja template.
- ansible/roles/llm-inference/tasks/monitoring.yml: removed the kubectl
get/patch/apply tasks and orphaned grafana-llm-dashboard.json.j2
template; role now only stands up node_exporter + nvidia_gpu_exporter
and verifies they're reachable — cluster-facing config lives in Git.
- host_vars/vars.yml + inventory.yml: finalize astro-orbiter as the
llama.cpp/RTX 3090 host (jarvis user, ssh key), drop stale Ollama/AMD
vars and ollama_server inventory group superseded by the ATX rebuild.
