llmgw/deploy/monitoring/README.md

# Watching a cluster

Prometheus, Alertmanager and Grafana, configured for what llmgw actually
publishes. Every alert here is written against a series this system emits;
nothing is aimed at a metric that might exist.

## What it is

One scrape target for the whole fleet.

Agents publish no metrics of their own. The control plane gathers what they
report — node state, memory, disk, engine queue depth, KV occupancy — and
republishes all of it, so a single endpoint describes every machine. That is
worth knowing before going looking for an exporter on each node.

## The port it scrapes

`metrics_listen`, not `admin_listen`.

The admin listener is bound to loopback for one reason: it also serves pprof,
and pprof can dump the process heap, where API keys sit in plaintext. Metrics
are the one thing on that listener something else genuinely needs to reach, so
they get a port of their own instead of becoming an argument for opening the
other one.

```yaml
# /etc/llmgw/server.yaml
metrics_listen: ":9091"
```

Confirm it carries nothing else:

```
curl -s -o /dev/null -w '%{http_code}\n' http://<control-plane>:9091/debug/pprof/   # 404
curl -s -o /dev/null -w '%{http_code}\n' http://<control-plane>:9091/api/v1/nodes   # 404
```

## Installing

On Ubuntu 24.04 the first two come from the archive; Grafana needs its own
repository.

```
apt-get install prometheus prometheus-alertmanager

install -m 0644 prometheus.yml            /etc/prometheus/prometheus.yml
install -m 0644 llmgw-rules.yml           /etc/prometheus/rules/llmgw.yml
install -m 0644 alertmanager.yml          /etc/prometheus/alertmanager.yml
promtool check config /etc/prometheus/prometheus.yml
systemctl restart prometheus prometheus-alertmanager

install -m 0644 grafana/datasource.yaml   /etc/grafana/provisioning/datasources/llmgw.yaml
install -m 0644 grafana/dashboards.yaml   /etc/grafana/provisioning/dashboards/llmgw.yaml
install -m 0644 -o grafana -g grafana grafana/llmgw-overview.json \
    /var/lib/grafana/dashboards/llmgw.json
systemctl restart grafana-server
```

The dashboard is provisioned from a file rather than clicked together, so it
survives a reinstall and can be reviewed in a diff.

## Where to run it

Not on the control plane. Monitoring that dies with the thing it monitors tells
you nothing at the moment you need it, and the control plane is also the busiest
machine in a small cluster.

Anywhere else on the management network will do. The mirror is a reasonable
host: it has the disk, and serving weights is bursty rather than constant.

## Nothing is sent anywhere

Alertmanager groups and holds alerts and has no receiver.

Where an alert should go — an address, a Slack workspace, a webhook — is a
decision with credentials attached, and a monitoring system that quietly starts
mailing people is worse than one that is visibly not wired up. Alerts are
visible at `:9093` and in Prometheus; add a receiver to `alertmanager.yml` to
make them travel. `critical` already routes separately so it can be pointed
somewhere else without touching the rest.

## Check that it fires

An alerting system nobody has seen fire is an assumption.

```
llmgw ctl cordon <node>     # work already there keeps running
# ~2 minutes later
curl -s http://<host>:9093/api/v2/alerts | jq '.[].labels'
llmgw ctl uncordon <node>   # the alert resolves on its own
```

Cordoning is the cheapest real test: it changes a metric the rules read, stops
nothing, and reverses in one command.

## What the alerts assume

**A stopped model publishes no series.** `llmgw_model_replicas_ready` exists
only for models with a replica placed, so `== 0` cannot fire for one that is
deliberately off. That is what makes an on-demand catalogue quiet here.

**Saturation of 1 is the healthy limit, not failure.** It is the worse of queue
depth and KV occupancy, measured by `ctl bench` rather than guessed. The alert
allows five minutes above it before saying anything.

**Latencies are in seconds.** These thresholds are written for CPU inference. A
p99 first token of thirty seconds is the alerting point here and would be
absurd on a GPU; change it when the hardware changes.

**Disk is only reported by nodes that hold weights.** A node with no model
directory reports nothing rather than zero, and the rule divides free by total
so a node that reports neither never fires.

## Where the metrics live

On the machine that scrapes them, in Prometheus's own store, and that is the
right answer at this size. Measured on this cluster: 2,359 series at 41 samples
a second, which compresses to roughly 7 MB a day — about 3 GB for a year.

```
# /etc/default/prometheus
ARGS="--storage.tsdb.retention.time=365d --storage.tsdb.retention.size=20GB"
```

A year because the questions worth asking of this data are seasonal: what did
capacity look like last quarter, was it always this slow, how much did the
fleet grow. Fifteen days answers none of them.

Both limits, not one. The time limit is the intent; the size cap is what stops
Prometheus becoming the thing that fills the disk if the series count grows
tenfold after somebody adds a fleet.

No remote write, no object store, no second tier. At two thousand series that
is infrastructure for a problem this cluster does not have, and every one of
those has its own failure modes to learn.

### The part that is not about capacity

The disk is not the constraint — 900 GB free against 3 GB a year. What matters
is what shares it.

On this cluster the model mirror and the metrics database are on the same
filesystem. A mirror that fills it stops Prometheus writing, so monitoring goes
quiet at exactly the moment the disk is the problem, and the alert that would
have said so is the one that died.

Two ways out, in order of how much they cost:

- Watch it, which is now done. `prometheus-node-exporter` arrives with the
  Prometheus package and was running, unscraped, on this machine — so the disk
  holding both was watched by nothing. It is a scrape target now, and
  `MonitoringDiskFilling` fires at fifteen percent rather than five, because
  the thing being protected is the ability to be told.
- Separate them: a volume of its own for `/var/lib/prometheus`, or monitoring
  on its own machine. Worth doing before the mirror holds a few hundred
  gigabytes; not worth doing today at seven percent used.

## What is not here

No exporter on the llmgw nodes, so no host CPU, load average or network for
them. The control plane publishes memory, disk and liveness for every node,
which is what placement decides on; the rest is a `node_exporter` away if
somebody wants it. The monitoring host itself is scraped, for the reason above.

No probe of the mirror. Its `/v1/health` is JSON rather than Prometheus text,
and checking it properly means `blackbox_exporter`.

No recording rules. At this size every query in the dashboard runs fast enough
raw, and a recording rule is a second definition of a number to keep in step
with the first.