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# Phase 6 — Dashboards and alerts as code
*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-5.md`](phase-5.md) · Next: [`phase-7.md`](phase-7.md)*
**Status:** Not started
**Message:** Depends on Phases 3–5 producing traces, logs and metrics worth
dashboarding.
**Time-box:** 2 evenings. This is an explicit requirement from Babak: *destroy and
recreate in seconds.*
### Concepts
- Three levels of "as code", and you should know when each applies:
1. **File provisioning** — YAML in `provisioning/datasources/` and
`provisioning/dashboards/`, plus dashboard JSON files mounted into the
container. Grafana loads them at startup. Simplest, no state, no API tokens,
perfect for a Compose demo. **This alone satisfies the requirement.**
2. **Grafana Foundation SDK** — typed libraries (Go, **Python**, TypeScript, Java,
PHP) that *generate* the dashboard JSON programmatically. Now a dashboard is a
function: `red_dashboard("ledger")`, called seven times in a loop. Reviewable
diffs, reusable panels, no 2000-line JSON blobs. Grafana now points here instead
of Grafonnet (which is legacy and unofficial).
3. **Terraform provider / Grafana Operator / Git Sync** — for state-managed,
multi-environment, or GitOps setups. Overkill here; the right answer *later*,
when this lands on your Kubernetes cluster.
- **Dashboards should answer questions, not display data.** A good service dashboard
answers, in order: is it up, is it serving, is it erroring, is it slow, and where
is the pressure. Panels that nobody looks at during an incident are cost, not value.
- **Alerts as code too.** Grafana alert rules, contact points and notification
policies all provision from YAML. And keep the *alert definition* next to the
dashboard that explains it.
### Resources
- Grafana docs → *Observability as code* (the index page — it lays out Foundation
SDK, file provisioning, Git Sync and Terraform, and tells you which to use when).
- Grafana Foundation SDK repo → the Python examples, especially the `red-method`
example.
- Udemy backbone: dashboard design sections (panel types, transformations,
variables, dashboard best practice).
### Build
Your platform provisions **datasources only** — there is no dashboards provider at
all. So this phase is entirely yours, and the right home for it is inside the
platform's own manifests (`k8s/grafana/`, the k3s port of the Ansible role),
using the same mechanism as everything else.
1. **Extend `k8s/grafana/`.** Add a file-based dashboard provider (a
`provisioning/dashboards/` YAML pointing at a mounted directory) and the
dashboard JSON. Ship both through `configMapGenerator`, exactly as
`datasources.yml` is shipped today, and mount them in `deployment.yaml`.
Two k8s-specific things to work out:
- A ConfigMap is capped at about 1 MiB, and client-side `kubectl apply`
also stores a copy in an annotation. Large generated dashboards push
against that.
- The configMap hash suffix rolls the Grafana pod on every change.
Decide whether that's what you want.
2. **Generate the JSON from code**, don't hand-write it. Use the **Grafana
Foundation SDK (Python)**: one function producing a RED dashboard for a given
service name, looped over the seven services; a second producing a system
overview (service graph, stream lag, pool saturation, error-budget burn). Commit
the generator *and* its output; `k8s/grafana/` ships the output.
3. **The demo is now `kubectl apply -k k8s/`.** Delete every dashboard through
the Grafana UI, re-apply (or go further: `kubectl delete -k k8s/` and rebuild
the whole platform), and watch them all come back.
That is a strictly stronger answer to Babak's "destroy and recreate in seconds"
than a local Makefile target, because it's the same command that builds the
platform.
4. While you're in there, review the provisioned datasources and add what's missing:
`tracesToMetrics` on Tempo (pointing at the Tempo-generated span metrics) is a
worthwhile addition, and the existing `tracesToLogsV2` has no `tags` mapping —
understand why `filterByTraceID: true` alone is sufficient here, and when it
wouldn't be.
5. Add alert rules — see Phase 8 for the Alertmanager-vs-Grafana-alerting choice.
**Done when:** `kubectl apply -k k8s/` restores every dashboard from scratch, and no
dashboard has ever been saved through the Grafana UI.