docs(observability): document ocr metrics, scrape edge, and access-log filter

- L2 container diagram now shows the Prometheus -> ocr:8000 scrape edge
  (plus the previously-undrawn Prometheus -> backend edge for symmetry).
- OBSERVABILITY.md gains a full ocr_* metrics table with labels, units,
  and the canonical example queries from issue #652.
- New "Internal-only endpoints" subsection captures the unauthenticated
  /metrics caveat and provides the Caddy block snippet for the case
  where the service ever gets a host port.
- Explicit note that MetricsPathFilter only quiets uvicorn stdout, and
  the OCR metrics must never carry PII or document content.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
This commit is contained in:
Marcel
2026-05-21 17:05:27 +02:00
parent 67368b4413
commit 2dbb3c37b4
2 changed files with 70 additions and 1 deletions

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@@ -118,11 +118,14 @@ To find a trace for a specific request in staging/production, either increase th
## Metrics (Prometheus → Grafana) ## Metrics (Prometheus → Grafana)
Prometheus scrapes the backend management endpoint every 15 s: Prometheus scrapes two targets every 15 s:
``` ```
Target: backend:8081/actuator/prometheus Target: backend:8081/actuator/prometheus
Labels: job="spring-boot", application="Familienarchiv" Labels: job="spring-boot", application="Familienarchiv"
Target: ocr:8000/metrics
Labels: job="ocr-service"
``` ```
All Spring Boot metrics carry the `application="Familienarchiv"` tag, which is how the Grafana Spring Boot Observability dashboard (ID 17175) filters to this service. All Spring Boot metrics carry the `application="Familienarchiv"` tag, which is how the Grafana Spring Boot Observability dashboard (ID 17175) filters to this service.
@@ -146,6 +149,70 @@ jvm_memory_used_bytes{area="heap", application="Familienarchiv"}
hikaricp_connections_active hikaricp_connections_active
``` ```
### OCR-service custom metrics
Exposed at `ocr:8000/metrics` by `prometheus-fastapi-instrumentator`. The
`http_*` metrics describe the FastAPI request layer; the `ocr_*` series are
domain-specific. **Never label these with PII or document content** — labels
have unbounded cardinality risk and are visible to anyone with Grafana access.
| Metric | Type | Labels | Unit | What it tracks |
|---|---|---|---|---|
| `ocr_jobs_total` | Counter | `engine` (`surya`/`kraken`), `script_type` | jobs | OCR jobs that started after a successful PDF download |
| `ocr_pages_total` | Counter | `engine` | pages | Successfully OCR'd pages in the streaming generator |
| `ocr_skipped_pages_total` | Counter | — | pages | Pages skipped because the engine raised on them |
| `ocr_words_total` | Counter | — | words | Recognized words summed across every block |
| `ocr_illegible_words_total` | Counter | — | words | Words below the confidence threshold (rendered as `[unleserlich]`) |
| `ocr_processing_seconds` | Histogram | `engine` | seconds | Per-page (stream) or per-document (`/ocr`) engine time, excluding preprocessing |
| `ocr_training_runs_total` | Counter | `kind` (`recognition`/`segmentation`), `outcome` (`success`/`error`) | runs | Completed training runs |
| `ocr_model_accuracy` | Gauge | `kind` | ratio (01) | Latest accuracy reported by a successful training run |
| `ocr_models_ready` | Gauge | — | 0\|1 | 1 once the lifespan startup has finished loading models |
Canonical example queries (the same ones referenced in issue #652):
```promql
# OCR throughput by engine
sum by (engine) (rate(ocr_pages_total[5m]))
# Share of words rendered as [unleserlich]
sum(rate(ocr_illegible_words_total[5m]))
/ sum(rate(ocr_words_total[5m]))
# p95 page processing time per engine
histogram_quantile(0.95, sum by (engine, le) (
rate(ocr_processing_seconds_bucket[5m])
))
# Training error rate
sum(rate(ocr_training_runs_total{outcome="error"}[1h]))
/ sum(rate(ocr_training_runs_total[1h]))
# Latest recognition vs segmentation accuracy
ocr_model_accuracy
```
### Internal-only endpoints
`/metrics` is exposed by the OCR service over plain HTTP without
authentication. The container is reachable only on the internal Docker
network — Caddy never proxies to it directly. If the service is ever
exposed (e.g. a `ports:` mapping is added), block the endpoint at the
reverse proxy:
```caddy
ocr.example.com {
@internal_only path /metrics /health
respond @internal_only 404
reverse_proxy ocr:8000
}
```
The `MetricsPathFilter` in `ocr-service/main.py` suppresses uvicorn's
**stdout** access log lines for `/metrics` and `/health` so the container
console stays focused on real OCR traffic. Promtail/Loki still receive
access lines from any other source. Treat the filter as console
noise-control, not an audit-suppression mechanism.
## Errors (GlitchTip) ## Errors (GlitchTip)
GlitchTip receives errors from both the backend (via Sentry Java SDK) and the frontend (via Sentry JavaScript SDK). It groups events by fingerprint, tracks first/last seen times, and links to the release that introduced the error. GlitchTip receives errors from both the backend (via Sentry Java SDK) and the frontend (via Sentry JavaScript SDK). It groups events by fingerprint, tracks first/last seen times, and links to the release that introduced the error.

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@@ -43,6 +43,8 @@ Rel(ocr, storage, "Fetches PDF via presigned URL", "HTTP / S3 presigned")
Rel(mc, storage, "Bootstraps bucket + service account on startup", "MinIO Client CLI") Rel(mc, storage, "Bootstraps bucket + service account on startup", "MinIO Client CLI")
Rel(promtail, loki, "Pushes log streams", "HTTP/Loki push API") Rel(promtail, loki, "Pushes log streams", "HTTP/Loki push API")
Rel(backend, tempo, "Sends distributed traces via OTLP", "HTTP / OTLP / port 4318 (archiv-net)") Rel(backend, tempo, "Sends distributed traces via OTLP", "HTTP / OTLP / port 4318 (archiv-net)")
Rel(prometheus, backend, "Scrapes JVM + HTTP metrics", "HTTP 8081 /actuator/prometheus")
Rel(prometheus, ocr, "Scrapes OCR + http_* metrics", "HTTP 8000 /metrics")
Rel(grafana, prometheus, "Queries metrics", "HTTP 9090") Rel(grafana, prometheus, "Queries metrics", "HTTP 9090")
Rel(grafana, loki, "Queries logs", "HTTP 3100") Rel(grafana, loki, "Queries logs", "HTTP 3100")
Rel(grafana, tempo, "Queries traces", "HTTP 3200") Rel(grafana, tempo, "Queries traces", "HTTP 3200")