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# Phase 2 — The model, and one signal end to end
*Part of `docs/roadmap/` — see [`intro.md`](intro.md) for platform/background context and [`summary.md`](summary.md) for how every phase fits together. Prev: [`phase-1.md`](phase-1.md) · Next: [`phase-3.md`](phase-3.md)*
**Status:** Not started
**Message:** Blocked on nothing — Phases 0 and 1 are done and the platform is
described above. Waiting to begin.
**Time-box:** one evening.
**Why:** you need the vocabulary, but more importantly you need to see one trace
appear in Grafana within an hour, so the rest of the roadmap feels concrete rather
than abstract.
### Concepts
- **Monitoring vs observability.** Monitoring answers questions you knew to ask
(known unknowns): dashboards and alerts built from predefined aggregates.
Observability is a property of the system: can you ask a *new* question about
production, that you never anticipated, without shipping new code? Charity Majors'
framing — monitoring is known-unknowns, observability is unknown-unknowns. The
practical implication for you: emit **wide, high-dimensional events** (rich span
attributes), not just pre-aggregated counters.
- **The OTel architecture split: API vs SDK vs Collector.**
- The **API** is what your code and third-party instrumentation libraries call.
If no SDK is configured, API calls are no-ops — that's deliberate, it means a
library can be instrumented without forcing a dependency on any implementation.
- The **SDK** is the engine: sampling, batching, context propagation, export.
Application owners configure the SDK; library authors only touch the API.
- The **Collector** is a standalone process that receives, processes and exports
telemetry. Optional, but you should use one.
- **OTLP** is the wire protocol — gRPC on 4317, HTTP/protobuf on 4318.
- **Resource** vs **attributes**: a Resource describes the *producer* (`service.name`,
`service.version`, `deployment.environment`) and is attached to every signal from
that process. Attributes describe the individual span/metric/log.
- **Semantic conventions**: standardised attribute names (`http.request.method`,
`db.system`, `server.address`). Use them for anything standard; namespace your own
(`ledgerline.account.id`). This is what makes cross-service, cross-language
correlation work — and it's what Grafana's prebuilt dashboards key off.
- **Signals**: traces, metrics, logs. (Profiling is a fourth signal, in alpha —
aware of, not learning yet.)
- **Why a Collector rather than exporting straight to Tempo/Loki/Prometheus:** your
app learns one endpoint. Swapping backends becomes a YAML edit, not a redeploy of
seven services. The Collector also does the things you don't want in your app:
retry, PII redaction, tail sampling, memory limiting, fan-out to multiple
destinations.
### Resources
- freeCodeCamp *OpenTelemetry Course* (~1 h, free) — watch at 1.5×, take notes on the
M.E.L.T. and context-propagation sections; skip the Node code.
- OpenTelemetry docs → Concepts → *Components* and *Signals*. ~30 min.
- Optional: run the OpenTelemetry Demo (`docker compose up` in the astronomy-shop
repo) once and click around Grafana/Jaeger for 20 minutes. Don't try to understand
it — just see what "done" looks like.
### Build
1. **Deploy the platform.** *Deployed 2026-10-12.* The mentor's Ansible
Grafana stack was ported to the k3s cluster `falken` as `k8s/`, keeping the
same versions, configs and pipeline. Deploy with `kubectl apply -k k8s/`.
`k8s/README.md` covers deploy/teardown, credentials and every deviation
from the Ansible role.
**Why not the Ansible route on a VM:**
- `czy` (1 GB) can't host it. The platform README recommends 2 vCPU / 4 GB.
- `*.vione.cloud` sits behind Cloudflare's proxy, which only forwards a few
ports (80/443, 8080, 8443, …), so raw ports like `:3000` never reach any
origin. That's why `ledgerline.vione.cloud:3000` showed nothing.
**Endpoints:** each one is a subdomain behind Traefik. Everything except
Grafana uses basic auth (`k8s/.credentials`).
| | |
|---|---|
| Grafana | https://grafana.vione.cloud |
| Prometheus | https://prometheus.vione.cloud |
| Alertmanager | https://alertmanager.vione.cloud |
| Loki | https://loki.vione.cloud |
| Tempo (query) | https://tempo.vione.cloud |
| Alloy UI | https://alloy.vione.cloud |
| OTLP/HTTP ingest | https://otlp.vione.cloud |
Container logs from `czy` reach Loki through an Alloy agent there (the
`alloy-agent` service in `docker-compose.traefik.yml`).
**Verified live:** all of the following worked, using a scratch trace sent
from `czy`.
- Every endpoint answers, and returns 401 without auth.
- Prometheus scrapes all six platform targets.
- Traces flow czy → Alloy → Tempo.
- Tempo's metrics-generator emits `traces_spanmetrics_*` and
`traces_service_graph_*` with exemplars.
- czy container logs land in Loki.
**Two platform bugs, fixed in the port.** As shipped, the Ansible role
produced no span metrics or service graph (Tempo needs
`metrics_generator.traces_storage`), and Prometheus discarded exemplars
(missing `--enable-feature=exemplar-storage`).
**One issue left open on purpose:** Tempo labels its exemplars `traceID`,
but the datasource's `exemplarTraceIdDestinations` expects `trace_id`.
Now open the Alloy UI and **read the component graph**. It shows you the
exact pipeline, including the fact that the OTLP receiver has only a traces
output. Seeing that in the UI before you get bitten by it is worth ten
minutes.
2. Pick the **`sanctions`** service (the smallest) and add nothing but zero-code
auto-instrumentation:
```
pip install opentelemetry-distro opentelemetry-exporter-otlp
opentelemetry-bootstrap -a install
```
and change its command to
`opentelemetry-instrument uvicorn services.sanctions.app:app --host 0.0.0.0 --port 8003`
with `OTEL_SERVICE_NAME=sanctions`,
`OTEL_EXPORTER_OTLP_ENDPOINT=https://otlp.vione.cloud`,
`OTEL_EXPORTER_OTLP_PROTOCOL=http/protobuf` — pointing at **Alloy**, not at
Tempo directly — plus the basic-auth header
`OTEL_EXPORTER_OTLP_HEADERS=Authorization=Basic%20<base64 user:pass>`
(URL-encoded: the space is `%20`; see `k8s/README.md`). Keep the
credential in the gitignored `.env.observability` on czy, not in compose.
3. Fire a request. Open Grafana → Explore → Tempo → find the trace.
**Done when:** you can see a single-service trace in Tempo, and you can explain out
loud what the Resource attributes on it mean and where they came from.