hermes-agent/docs/observability/monitoring.md
2026-07-24 19:54:08 +00:00

194 lines
8.5 KiB
Markdown

# Gateway Monitoring
Service health monitoring plus structured operational diagnostics for the
Hermes gateway daemon, exported over OTLP/HTTP to an operator-configured
endpoint (OpenTelemetry Collector, DataDog, or any OTLP receiver).
This plane is content-free by construction. It exports gateway and cron
lifecycle state, platform connector health, and content-free warning/error
diagnostics. It never exports prompts, messages, tool arguments or results,
job names, destinations, schedules, raw errors, session history, usage
analytics, audit logs, or detailed execution traces. Run/model/tool trajectory
capture is a separate plane served by the NeMo Relay integration
(`plugins/observability/nemo_relay/`) and its Hermes-owned subscribers.
## What gets exported
| Signal | OTLP route | Content |
| --- | --- | --- |
| Gateway gauges | `/v1/metrics` | `hermes.gateway.up/state/busy/drainable/active_agents/restart_requested`, `hermes.platform.up/degraded` with bounded `error_code` attributes |
| Health/lifecycle events | `/v1/traces` | `gateway.lifecycle` state transitions (`starting -> running -> draining -> stopped`, `startup_failed`, exit), `gateway.health_snapshot`, platform state changes |
| Diagnostics | `/v1/logs` | Warning/error gateway events with a constant body and bounded subsystem, severity, error class, and error code attributes; rendered log messages are never exported |
| Cron scheduler gauges | `/v1/metrics` | Ticker heartbeat and last-success age (omitted when unavailable), a monotonic catch-up-occurrence count from the scheduler's stale-window branch, enabled/running job counts, and overdue count derived from persisted `next_run_at` plus the scheduler's existing grace rule |
| Cron execution lifecycle | `/v1/traces` | Durable `claimed/running/completed/failed/unknown` states, bounded source and error class, opaque hashed job key, elapsed duration when timestamps exist, and delivery outcome when the scheduler knows it; terminal states make a fail-open flush attempt that can delay completion by up to one second |
Signals carry `service.name`, version, supervision mode, and a stable one-way
hash of the install id so an operator can distinguish instances without
exporting account/profile identity or the raw install identifier.
## Enabling
```yaml
# config.yaml
monitoring:
gateway_health_export:
enabled: true
export:
otlp:
enabled: true
endpoint: http://collector-host:4318/v1/traces # metrics/logs derive
headers_env: {} # header name -> ENV VAR NAME (values never stored)
```
Check the posture any time:
```bash
hermes monitoring status
```
The OpenTelemetry SDK is an optional extra (`pip install 'hermes-agent[otlp]'`),
lazy-installed on first use. When the SDK is missing or the endpoint is down,
the gateway runs unaffected: metric collection and ordinary event export stay
off the hot path, while terminal cron events make one bounded fail-open flush
attempt of up to one second so the final state is less likely to be lost.
Works identically under systemd/launchd/s6 supervision, containers, tmux, or
a plain `hermes gateway run`: the exporter lives in the gateway process, so
no sidecar, agent, or collector is required on the host.
## Collecting into DataDog
Run a customer-owned OpenTelemetry Collector and forward:
```yaml
# otel-collector config
receivers:
otlp:
protocols:
http:
exporters:
datadog:
api:
key: ${env:DD_API_KEY}
service:
pipelines:
metrics: {receivers: [otlp], exporters: [datadog]}
traces: {receivers: [otlp], exporters: [datadog]}
logs: {receivers: [otlp], exporters: [datadog]}
```
Point `monitoring.export.otlp.endpoint` at the collector. Alerts belong on
`hermes.gateway.up`, `hermes.platform.up`, and `hermes.platform.degraded`.
## Generic fleet queries and alerts
The exact syntax depends on the customer's observability backend. The examples
below use PromQL-style expressions and intentionally avoid vendor-specific
routing, destinations, or customer inventory.
Group fleet views by the opaque `service.instance.id` resource attribute. A
process that has died cannot emit its own zero, so every deployment needs both
explicit-state and missing-series detection.
```promql
# Explicit gateway failure.
hermes_gateway_up == 0
# Box disappeared or stopped exporting. Choose a window longer than the
# configured export interval and collector retry allowance.
absent_over_time(hermes_gateway_up[5m])
# Locally owned bridge is explicitly down.
hermes_platform_up == 0
# Scheduler thread is stale even though the gateway may still be alive.
hermes_cron_scheduler_heartbeat_age_seconds > 180
# Ticker loops but has not completed a successful tick recently.
hermes_cron_scheduler_last_success_age_seconds > 300
# One or more jobs are beyond their existing scheduler grace window.
hermes_cron_jobs_overdue > 0
# Catch-up counter increased, proving at least one stale occurrence was
# collapsed and run once after a delay.
increase(hermes_cron_scheduler_catch_up_occurrences[15m]) > 0
```
Cron execution lifecycle records arrive as `hermes.cron_execution` spans.
Alert or derive events from bounded attributes such as:
```text
hermes.status = failed|unknown
hermes.delivery_outcome = failed|not_configured
hermes.error_class = auth_failed|rate_limited|timeout|network_error|
dispatch_failed|interrupted|empty_response|
invalid_config|unknown
```
Recommended operator views:
1. one row per `service.instance.id` with gateway and configured local-platform
state;
2. scheduler heartbeat, last-success age, running count, overdue count, and
catch-up increase;
3. a cron lifecycle feed keyed only by opaque `hermes.job_key`;
4. separate alerts for box absence, local bridge down, scheduler stale, cron
failed/unknown, delivery failure, and overdue/catch-up activity.
Keep alert thresholds and routing in deployment-owned configuration. Do not add
job names, prompts, outputs, schedules, destinations, raw errors, profile names,
or account identity merely to make a dashboard easier to read.
## Release-validation scenarios
Before accepting a deployment, force and verify all five cases through the real
collector and backend:
1. **Cron success:** observe `claimed -> running -> completed`, duration, and a
truthful delivery outcome.
2. **Cron failure:** observe `failed` plus a bounded error class, with no raw
exception or content in the decoded OTLP payload.
3. **Cron interruption:** stop the owning gateway during execution, restart it,
and observe recovery to `unknown`.
4. **Locally owned bridge outage:** break one native connector, observe its
bounded down/retrying/fatal state and recovery, and verify unaffected boxes
remain healthy.
5. **Killed gateway:** terminate one canary, verify missing-series detection,
restart it, and confirm the same opaque instance identity returns.
Hermes Agent-owned Relay transport health remains in scope. A separate gateway
or connector service remains authoritative for any shared connected-platform
state that it owns and should export that state through its own telemetry path.
For every scenario, verify the signal and alert clear on recovery, other boxes
remain unaffected, collector failure stays fail-open, and decoded metrics,
spans, logs, and resource attributes remain content-free.
## Local smoke test (no Docker)
```bash
# terminal 1: capture collector on :4318
python scripts/observability/otel_capture_collector.py \
--host 127.0.0.1 --port 4318 --log /tmp/hermes_otel_capture.jsonl
# terminal 2: drive the real exporter through lifecycle transitions,
# a fatal platform, and a structured warning event, then flush
python scripts/observability/gateway_health_export_probe.py \
--endpoint http://127.0.0.1:4318/v1/traces \
--log /tmp/hermes_otel_capture.jsonl --wait 8
# exit 0 prints: {"requests": 6, "paths": ["/v1/logs", "/v1/metrics", "/v1/traces"]}
```
## Boundaries and roadmap
The `hermes monitoring` CLI intentionally exposes `status` only. This first
release covers only Hermes Agent-owned service-health and operational-diagnostic
signals, including Hermes Agent-owned Relay transport health. Team Gateway's
authoritative shared connector/platform state is explicitly out of scope, as
are product analytics, audit/quality reporting, and detailed execution traces.
Shared client usage metrics and enterprise trace telemetry are being designed on
the NeMo Relay integration with their own consent, policy, and export
boundaries; this monitoring plane stays narrow so an operator can enable it
without touching any content-bearing signal. The telemetry surface may be
reorganized as that lands.