# 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:** In progress **Message:** Started 2026-10-12. Step 1 (deploy the platform) is done and verified live, apart from reading the Alloy component graph. Next: step 2, zero-code auto-instrumentation of `sanctions`. **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` (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.