feat(sdlc): staging environment + automated staging→prod pipeline
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- pr-checks.yml: PR gate — frontend typecheck+jest, backend import smoke, image builds (no push), Claude AI review posted as PR comment (severe findings block merge) - deploy.yml (replaces build-and-push.yml): merge to main builds+pushes images tagged sha-<sha>/staging, deploys the staging Portainer stack via webhook, runs Playwright E2E journeys against staging, then retags the verified images :prod (previous kept as :prod-previous) and deploys prod - docker-compose.portainer.staging.yml: second Portainer stack — :staging images, sc_staging_* names, own macvlan IPs, Airflow on 8081; data bootstrapped from source via the staging Airflow DAGs - prod compose now pins :prod instead of :latest (only the promotion step moves it; :latest is no longer published) - e2e/: 6 Playwright journeys (search, postcode, detail, compare, rankings) driven by BASE_URL — the promotion gate - scripts/ci/ai_review.py: Claude review with structured JSON findings - docs/DEPLOY.md: full SDLC doc incl. one-time setup checklist and rollback - replaced removed 'next lint' with tsc typecheck; fixed stale jest tests (slug URLs, N/A formatting, stable trend, fake-timer setup) Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01PqGhF93UrpDNvXBLMjJENL
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# SDLC & Deployment Pipeline
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SchoolCompare uses a fully automated staging → production pipeline on Gitea
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Actions. AI writes the code on feature branches; the pipeline verifies every
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change on a staging environment before promoting the exact same images to
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production. Human input is directional only: feature requests, PR review if
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desired, and intervention when a gate fails.
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## The flow
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```
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feature branch (AI-authored)
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│ PR to main
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▼
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PR checks (.gitea/workflows/pr-checks.yml)
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typecheck + unit tests + backend smoke + image builds (no push)
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+ Claude code review posted as a PR comment (severe findings fail the check)
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│ merge (branch protection requires green checks)
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▼
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Deploy pipeline (.gitea/workflows/deploy.yml)
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1. build & push images → tags sha-<sha>, staging
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2. staging Portainer webhook → wait for staging health
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3. Playwright E2E journeys against staging
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4. retag sha-<sha> → :prod (same bytes — build once, promote the image)
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previous :prod saved as :prod-previous
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5. prod Portainer webhook → wait for prod health
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```
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Key principle: **build once, promote the exact image**. Production pins `:prod`,
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which only moves after the E2E gate passes on staging. Nothing tags `:latest`
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anymore.
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## Branch & PR workflow
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- `main` is protected: no direct pushes, PRs require green status checks.
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- All work (human or AI) happens on feature branches → PR to `main`.
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- Merging to `main` **is** the release action. If staging or the E2E gate
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fails, production is untouched.
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## Environments
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| | Production | Staging |
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|---|---|---|
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| Portainer stack file | `docker-compose.portainer.yml` | `docker-compose.portainer.staging.yml` |
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| Image tag | `:prod` | `:staging` |
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| Container prefix | `sc_` / `schoolcompare_` | `sc_staging_` |
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| Frontend macvlan IP | 10.0.1.150 | `STAGING_FRONTEND_IP` (default 10.0.1.151) |
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| Postgres macvlan IP | 10.0.1.189 | `STAGING_DB_IP` (default 10.0.1.190) |
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| Airflow UI port | 8080 | 8081 |
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| Volumes | stack-prefixed | stack-prefixed (fully isolated) |
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Staging gets `:staging` images on every merge to main — even ones that later
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fail the E2E gate. That's the point: staging absorbs the risk.
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## Gitea repository secrets
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| Secret | Purpose |
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|---|---|
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| `REGISTRY_TOKEN` | push images to privaterepo.sitaru.org (already set) |
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| `ANTHROPIC_API_KEY` | Claude PR review (`scripts/ci/ai_review.py`) |
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| `GITEA_TOKEN` | post PR review comments (needs issue-comment scope) |
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| `PORTAINER_STAGING_WEBHOOK` | staging stack redeploy webhook URL |
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| `PORTAINER_PROD_WEBHOOK` | production stack redeploy webhook URL |
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| `STAGING_BASE_URL` | e.g. `http://10.0.1.151:3000` — health poll + E2E target |
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| `PROD_BASE_URL` | e.g. `http://10.0.1.150:3000` — post-promotion health poll |
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## One-time setup checklist
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1. **Create the staging stack** in Portainer from
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`docker-compose.portainer.staging.yml` (stack name e.g.
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`schoolcompare-staging`). Set the same environment variables as prod plus
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`STAGING_DB_IP` / `STAGING_FRONTEND_IP` if the defaults clash.
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2. **Enable webhooks** on both stacks (Portainer → Stack → Webhook) and store
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the URLs as `PORTAINER_STAGING_WEBHOOK` / `PORTAINER_PROD_WEBHOOK`. Remove
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the old hardcoded webhook usage (now gone from the workflows).
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3. **Add the remaining secrets** listed above in Gitea → repo → Settings →
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Actions → Secrets.
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4. **Protect `main`** in Gitea → Settings → Branches: require PRs, require the
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pr-checks status checks (frontend, backend, builds, ai-review) to pass.
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5. **Bootstrap staging data via Airflow** (no prod dump — staging populates
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itself from source, exercising the pipeline image end-to-end):
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- Open the staging Airflow UI (`http://<host>:8081`) and trigger, in order:
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`school_data_daily`, `school_data_monthly_ofsted`,
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`school_data_monthly_parent_view`, then the manual-schedule
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`school_data_annual_ees` and `school_data_annual_idaci`.
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- First runs download from government sources (GIAS, Ofsted, EES, IDACI),
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run dbt, and sync Typesense — expect the initial backfill to take a while.
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- The scheduled DAGs then keep staging fresh exactly like prod.
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6. **Switch the prod stack to `:prod` tags** — the repo's
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`docker-compose.portainer.yml` is already updated; redeploy the prod stack
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from it. Until the first pipeline run promotes an image, tag the current
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images manually: `docker buildx imagetools create -t <image>:prod <image>:latest`
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for each of the three images.
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## Rollback
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Every promotion first re-points `:prod-previous` at the outgoing `:prod`.
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To roll back:
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```bash
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for img in backend frontend pipeline; do
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docker buildx imagetools create \
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-t privaterepo.sitaru.org/tudor/school_compare-$img:prod \
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privaterepo.sitaru.org/tudor/school_compare-$img:prod-previous
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done
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curl -fsSk -X POST "$PORTAINER_PROD_WEBHOOK"
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```
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Or promote any older build directly: `imagetools create -t <image>:prod <image>:sha-<shortsha>`.
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## E2E suite
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Lives in `e2e/` (own package — CI installs it without the app's node_modules).
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Journeys: home + name search, postcode search, school detail, two-school
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comparison, rankings table. Run locally against any environment:
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```bash
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cd e2e && npm ci
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BASE_URL=http://10.0.1.151:3000 npx playwright test
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```
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Tests assert data invariants (results exist, charts render), not exact
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numbers, so scheduled data refreshes don't break the gate.
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## AI code review
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`scripts/ci/ai_review.py` sends the PR diff to Claude (`claude-opus-4-8`),
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posts the structured findings as a PR comment, and fails the check only when a
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finding is rated **severe** (would break prod, leak data, or corrupt data).
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Minor findings are informational and never block a merge.
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