docs: add Prometheus + Grafana setup notes and portal metrics plan

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jester 2026-02-07 21:47:41 +00:00
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# 2026-02-07 — Prometheus + Grafana (LXC node_exporter) status
## What works right now
- Each LXC template has **node_exporter** installed.
- Prometheus is scraping container exporters via **HTTP service discovery** from the API.
- Grafana can display metrics using a standard Node Exporter dashboard (and a custom "ZLH LXC Overview" dashboard).
## Prometheus config (current)
On `zlh-monitor`:
`/etc/prometheus/prometheus.yml` includes a dynamic job:
```yaml
- job_name: 'zlh_lxc'
scrape_interval: 15s
http_sd_configs:
- url: http://10.60.0.245:4000/sd/exporters
refresh_interval: 30s
authorization:
type: Bearer
credentials: '<TOKEN>'
```
This is why containers show up even though there are no hardcoded container IPs.
### The earlier failure mode
Prometheus log showed:
* `dial tcp 10.60.0.245:80: connect: connection refused`
That happened when the SD URL was missing the port (or using the wrong path). Correct is `:4000/...` (or whatever the API listens on).
## Grafana dashboard import gotcha
When importing JSON dashboards:
* If the JSON references a datasource UID that does not exist (example error: **"Datasource PROM was not found"**),
you must either:
* select the real datasource during import, or
* edit the dashboard JSON datasource UID to match your Grafana datasource UID.
Once the datasource was mapped, the "ZeroLagHub - LXC Overview" dashboard started drawing data.
## CPU mismatch vs `top` (note)
You observed CPU% in Grafana not matching what `top` was showing.
This can be normal depending on:
* how CPU is computed (rate window, per-core vs normalized, cgroup accounting in containers, etc.)
* dashboard query math (e.g. averaging across cores)
We decided not to block on perfect parity right now — the dashboard is good enough for:
* "is it pegged?"
* "is it trending up/down?"
* "is this instance dead?"
If we need tighter parity later:
* validate the container is exporting the right counters
* compare `node_cpu_seconds_total` raw series
* consider container-aware exporters/cAdvisor (optional)
## Next step (portal)
Goal:
* show "CPU / RAM / Disk / Net" indicators on the portal server cards.
Two practical routes:
1. **Query Prometheus from API** (recommended)
* API calls Prometheus HTTP API (server-side)
* portal calls API
* avoids exposing Prometheus or Grafana to end users
2. **Embed Grafana panels** (works, but needs careful auth + iframe settings)
* useful for internal admin views
* more risk for multi-tenant UI unless you add strict access control
Short-term plan:
* build API endpoints like:
* `GET /api/metrics/servers/:vmid/summary`
* returns a small payload suitable for server cards:
* cpu_percent
* mem_percent
* disk_percent
* net_in/out (rate)
## Quick PromQL building blocks (reference)
CPU (percent used, 5m window):
```promql
100 - (avg by (instance) (rate(node_cpu_seconds_total{mode="idle"}[5m])) * 100)
```
Memory (percent used):
```promql
100 * (1 - (node_memory_MemAvailable_bytes / node_memory_MemTotal_bytes))
```
Disk (percent used, excluding tmpfs/overlay):
```promql
100 * (1 - (node_filesystem_avail_bytes{fstype!~"tmpfs|overlay"} / node_filesystem_size_bytes{fstype!~"tmpfs|overlay"}))
```
Network in/out:
```promql
sum by (instance) (rate(node_network_receive_bytes_total{device!~"lo"}[5m]))
sum by (instance) (rate(node_network_transmit_bytes_total{device!~"lo"}[5m]))
```
If your SD labels include `vmid`, prefer grouping by `vmid`.