fix: repair main build breakage (65 TS errors) + smoke-test verification

[devin-ai-integration]

Summary

After all feature branches were consolidated into main, the merged tree did not compile — tsc --noEmit reported 65 errors and vitest had 1 failing test. The Caddy edge-gateway commit and the Drizzle query/enhancement helpers were authored against assumptions that didn't hold once merged. This PR repairs that breakage so main is functional (compiles, builds, tests pass) and adds a smoke test proving the auth → DB round-trip works against real Postgres.

Root causes & fixes

1. Logger arg order (caddy-service.ts, caddy-router.ts, db-enhancements.ts)
The project's logger wrapper is logger.info(message, context), but these files used pino's native logger.info(obj, message). All call sites corrected:

- logger.info({ serverId, routeId }, "Caddy route added");
+ logger.info("Caddy route added", { serverId, routeId });

2. db-queries.ts referenced columns that don't exist in the schema (35 errors)
The query builders assumed a different schema. Mapped every reference to the real Drizzle columns, e.g.:

• users.name/users.phone → users.firstName/users.lastName/users.phoneNumber
• farms.name → farms.farmName
• harvests.farmId/harvests.totalValue → harvests.userId/harvests.revenue
• carbonCredits.quantity/pricePerTon → carbonCredits.tonnes / project pricePerTonne
• iotReadings.soilMoisture/... (columns don't exist — generic metric/value model) → conditional CASE WHEN metric = '...' THEN value aggregations
• pipelineMetrics.recordsWritten/throughputRps → CASE WHEN metricName = '...' over metricValue
• federatedParticipants.contributionScore/localDataSize → localAccuracy/dataPoints
• carbonProjects.annualSequestration → annualCredits
• marketPrices/harvests timestamp comparisons: pass Date objects instead of date strings

3. db-enhancements.ts used array destructuring on a QueryResult (node-postgres)
getDb() uses drizzle-orm/node-postgres, whose db.execute() returns { rows }, not an array:

- const [connStats] = await this.db.execute(sql`...`);
+ const { rows: connRows } = await this.db.execute(sql`...`);

The corresponding unit-test mock was returning a bare array (wrong shape for this driver); updated it to return { rows: [...] }.

4. Vitest could not load the suite (@dapr/dapr)
The real @dapr/dapr ships an ESM proto file inside a CommonJS package, which Vitest's loader can't parse. Added a test-only alias in vitest.config.ts → tests/mocks/dapr-stub.ts exposing the same surface used by server/dapr-client.ts. Production imports the real package unchanged.

Verification

• npx tsc --noEmit → 0 errors
• npx vitest run → 1076 passed, 30 skipped, 0 failed
• npm run build → builds dist/index.js + PWA (321 precache entries)
• Full dev server boots (Vite :3000, API :3001); Redis/Kafka absent → graceful fallback
• Smoke test against real Postgres: auth.register → row persisted (users.id=367) → auth.login → JWT-protected auth.me returns the user; protected endpoints correctly return 401 without a token (middleware enforced)

Notes

• The @dapr/dapr stub is strictly a test-loader workaround — it does not establish production Dapr runtime behavior.
• 30 skipped tests are all in phase118-integration.test.ts (require live external infra).

Link to Devin session: https://app.devin.ai/sessions/87560355a8b7425392cbfab1aa9e89fa
Requested by: @munisp

[devin-ai-integration]

Original prompt from Patrick

https://drive.google.com/file/d/1xoRlAMbf0QPI9WGN9K11iXEDhsTCgf_0/view?usp=sharing
https://drive.google.com/file/d/1kpaWHhlZq1410zZdqm87cSkY8MNvMOLI/view?usp=sharing
Extract ALL the files and artifact. Analyse and perform the following
1)
1)how robust and integrated is postgres ?
2)how robust and integrated is tigerbeetle ?
3)how robust and integrated is redis ?
4)how robust and integrated is mojaloop ?
5) how robust and integrated is kafka ?
6)how robust and integrated is apisix ?
7)how robust and integrated is keycloak ?
8)how robust and integrated is openappsec ?
9)how robust and integrated is permify ?
10)how robust and integrated is opensearch ?
11) how robust and integrated is fluvio ?
12. How robust and integrated is dapr
2)implement all the gaps and recommendation
3)how do ensure and assess that features for example domain and business logic/rules/requirements are fully impemented and production ready and complete - can you thoroughly assess each files and features to determine there are ready for production

1. Database integration (replace in-memory with real Postgres)
2. Inter-service HTTP wiring with retries/circuit breakers
3. Security hardening (JWT everywhere, remove hardcoded creds, mTLS)
4. Integration tests for critical flows
5. Graceful shutdown, observability, alerting
6. inter-service grpc wiring with retries/circuit breakers

4)search for orphan, partially and generic scaffolded features across the platform - fully implement them end to end -generic CRUD-only patterns , modules with no domain logic, disconnected features, and incomplete implementations.

[devin-ai-integration]

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