FieldTrack 2.0 Backend — Walkthrough

Phase 0 — Project Scaffolding

Fastify + TypeScript backend scaffold with JWT, structured logging, modular routing, Docker, and domain placeholders.

Deviation: replaced ts-node-dev with tsx watch (ESM compat) and added pino-pretty dev dep.

Phase 1 — Secure Tenant Isolation Layer

Files Changed / Created

File	Action	Purpose
jwt.ts	NEW	Zod v4 schema for JWT payload (`sub`, `role`, `organization_id`)
global.d.ts	MODIFIED	Wires `JwtPayload` into Fastify types + adds `organizationId` to request
auth.ts	MODIFIED	JWT verify → Zod validate → attach tenant context (or 401)
tenant.ts	NEW	`enforceTenant()` — scopes any query to `request.organizationId`

How Tenant Enforcement Works

sequenceDiagram
    participant Client
    participant Middleware as auth.ts
    participant Zod as jwt.ts (Zod)
    participant Handler as Route Handler
    participant DB as Supabase

    Client->>Middleware: Request + JWT
    Middleware->>Middleware: jwtVerify() — signature check
    Middleware->>Zod: safeParse(decoded payload)
    alt Invalid claims
        Zod-->>Middleware: validation errors
        Middleware-->>Client: 401 + error details
    else Valid claims
        Zod-->>Middleware: typed JwtPayload
        Middleware->>Middleware: request.organizationId = payload.organization_id
        Middleware->>Handler: proceed
        Handler->>DB: enforceTenant(request, query)
        Note over DB: .eq("organization_id", request.organizationId)
        DB-->>Handler: tenant-scoped data only
    end

Key guarantees:

No trust without validation — decoded JWT is always schema-checked via Zod
Tenant context is mandatory — missing organization_id → 401
Role enforcement — only ADMIN or EMPLOYEE accepted
Query-level isolation — enforceTenant() ensures all DB queries are org-scoped
Type safety everywhere — request.user and request.organizationId are fully typed

Phase 2 — Attendance Module (Check-in / Check-out)

Architecture: Route → Controller → Service → Repository

flowchart LR
    A["Client"] --> B["attendance.routes.ts"]
    B -->|"auth + role guard"| C["attendance.controller.ts"]
    C --> D["attendance.service.ts"]
    D -->|"business rules"| E["attendance.repository.ts"]
    E -->|"enforceTenant()"| F["Supabase"]

Files Created

File	Layer	Purpose
attendance.schema.ts	Types	DB row type, Zod pagination schema, response interfaces
attendance.repository.ts	Repository	Supabase queries — all scoped via `enforceTenant()`
attendance.service.ts	Service	Business rules: no duplicate check-in, no check-out without open session
attendance.controller.ts	Controller	Extract request data, call service, return `{ success, data }`
attendance.routes.ts	Routes	4 endpoints with auth middleware, ADMIN guard on org-sessions
supabase.ts	Config	Supabase client singleton (service role key)
role-guard.ts	Middleware	Reusable `requireRole()` factory — 403 on role mismatch
errors.ts	Utils	Added `ForbiddenError` (403)

Endpoints

Method	Path	Auth	Description
POST	`/attendance/check-in`	JWT	Check in (rejects if open session exists)
POST	`/attendance/check-out`	JWT	Check out (rejects if no open session)
GET	`/attendance/my-sessions`	JWT	Employee's own sessions (paginated)
GET	`/attendance/org-sessions`	JWT + ADMIN	All org sessions (paginated)

Business Rules

EMPLOYEE: Can only check in if no open session; can only check out if an open session exists; cannot see other users' sessions
ADMIN: Can view all sessions in their org via /org-sessions; cannot access other orgs
Tenant isolation: Every DB query passes through enforceTenant(), enforcing .eq("organization_id", ...)
Query chain: enforceTenant() is called before terminal operations (.single(), .range()) to preserve the filter builder type

Example curl Requests

# Check in (requires valid JWT)
curl -X POST http://localhost:3000/attendance/check-in \
  -H "Authorization: Bearer <JWT_TOKEN>"

# Check out
curl -X POST http://localhost:3000/attendance/check-out \
  -H "Authorization: Bearer <JWT_TOKEN>"

# My sessions (paginated)
curl "http://localhost:3000/attendance/my-sessions?page=1&limit=20" \
  -H "Authorization: Bearer <JWT_TOKEN>"

# Org sessions (ADMIN only)
curl "http://localhost:3000/attendance/org-sessions?page=1&limit=20" \
  -H "Authorization: Bearer <ADMIN_JWT_TOKEN>"

Verification Results

Check	Result
`npm run build` (tsc)	✅ Zero errors
`npm run dev` (tsx watch)	✅ Server starts on `0.0.0.0:3000`
`GET /health`	✅ `{"status":"ok","timestamp":"..."}`

Phase 3 — Location Ingestion System

Files Created

File	Layer	Purpose
locations.schema.ts	Types	DB row type, Zod schema (`latitude`, `longitude`, `accuracy`, `recorded_at`), response interfaces
locations.repository.ts	Repository	Supabase `createLocation` and `findLocationsBySession`, scoped via `enforceTenant()`
locations.service.ts	Service	Business rules: verify open attendance session before insertion
locations.controller.ts	Controller	Extract request data, Zod payload validation, delegate to service, format responses
locations.routes.ts	Routes	2 endpoints, both restricted to `EMPLOYEE` via role guard

Endpoints

Method	Path	Auth	Description
POST	`/locations`	JWT + EMPLOYEE	Record GPS point (body: lat, lng, acc, recorded_at)
GET	`/locations/my-route?sessionId=...`	JWT + EMPLOYEE	Get ordered location history for an active/past session

Business Rules

Attendance Dependency: An employee must have an open attendance session (checked via attendanceRepository.findOpenSession) to record a location.
Time Validation: recorded_at cannot be more than 2 minutes in the future (enforced via Zod refinement).
Coordinate Bounds: Latitude between -90 and 90, Longitude between -180 and 180.
Role Guarding: Location ingestion is strictly limited to EMPLOYEE role. ADMIN cannot POST locations on behalf of an employee.

Suggested Database Indexes (Phase 3 Prep)

Since findLocationsBySession orders by recorded_at, and queries are scoped to session_id, the locations table requires the following index in PostgreSQL to remain performant at scale:

CREATE INDEX idx_locations_session_recorded_at ON locations(session_id, recorded_at ASC);

If tenant-scoped analytics are added in the future over raw locations, a broader compound index will be needed:

CREATE INDEX idx_locations_tenant_search ON locations(organization_id, user_id, recorded_at DESC);

Example curl Requests

# Record location (requires open attendance session)
curl -X POST http://localhost:3000/locations \
  -H "Authorization: Bearer <EMPLOYEE_JWT>" \
  -H "Content-Type: application/json" \
  -d '{
    "latitude": 37.7749,
    "longitude": -122.4194,
    "accuracy": 15.5,
    "recorded_at": "2026-03-03T10:00:00Z"
  }'

# Get location route for an existing session
curl "http://localhost:3000/locations/my-route?sessionId=a1b2c3d4-..." \
  -H "Authorization: Bearer <EMPLOYEE_JWT>"

Phase 4 — Location Bulk Ingestion (Production-Optimized)

Architecture Upgrade

Upgraded location ingestion from single-inserts to a highly optimized bulk-insert pattern, handling offline batching and high-frequency GPS tracking efficiently.

Additional Endpoint

Method	Path	Auth	Description
POST	`/locations/batch`	JWT + EMPLOYEE	Bulk ingest up to 100 points simultaneously

Batch Payload Schema

{
  "session_id": "9b1deb4d-3b7d-4bad-9bdd-2b0d7b3dcb6d",
  "points": [
    {
      "latitude": 37.7749,
      "longitude": -122.4194,
      "accuracy": 5.0,
      "recorded_at": "2026-03-03T10:00:00Z"
    }
  ]
}

Enterprise Optimizations & Business Rules

1️⃣ Idempotency (Mobile Retries): The database uses an UPSERT on (session_id, recorded_at) combined with { ignoreDuplicates: true }. If the mobile client retries a batch due to a poor network connection, duplicates are cleanly discarded directly at the database layer. This guarantees route reconstruction isn't corrupted by duplicate points.
2️⃣ Zero Write Amplification: Instead of hitting the DB to scan for the user's active session on every GPS pulse, the client provides the session_id directly in the payload. The backend executes an extremely lightweight O(1) primary key validation (validateSessionActive) to confirm ownership and activity, slicing database CPU usage drastically compared to iterative scanning.
3️⃣ Per-User Rate Limiting: Protected by Fastify's native @fastify/rate-limit plugin. A custom keyGenerator decodes the JWT sub directly from the Authorization header during the fast onRequest lifecycle. The batch location ingest vector strictly drops combinations exceeding 10 requests every 10 seconds, stopping malicious overload attacks instantaneously.
4️⃣ Telemetry & Metrics Logging: Both single and batch endpoints track executing latency via Node's performance.now(). Additionally, during bulk ingestion, the service calculates and logs the exact number of duplicatesSuppressed by comparing payload length against the successful database insert count.
Strict Validation: Zod array limits (min(1).max(100)) prevent abuse. If even a single point in the payload violates rules, the entire batch is rejected (400 Bad Request).
Single Read / Single Write: Validations verify the session hits the database exactly once. The insert operation maps all points and calls Supabase .upsert([...rows]) to perform the bulk operation in a single network trip.

Example Batch curl Request

curl -X POST http://localhost:3000/locations/batch \
  -H "Authorization: Bearer <EMPLOYEE_JWT>" \
  -H "Content-Type: application/json" \
  -d '{
    "session_id": "9b1deb4d-3b7d-4bad-9bdd-2b0d7b3dcb6d",
    "points": [
      {
        "latitude": 37.7749,
        "longitude": -122.4194,
        "accuracy": 5.0,
        "recorded_at": "2026-03-03T10:00:00Z"
      },
      {
        "latitude": 37.7750,
        "longitude": -122.4195,
        "accuracy": 4.5,
        "recorded_at": "2026-03-03T10:00:05Z"
      }
    ]
  }'

Suggested Database Schema & Partitioning Strategy

For this level of enterprise ingestion, the locations table requires specific indexing:

-- 1) Guaranteed Idempotency (critical for Supabase onConflict)
CREATE UNIQUE INDEX uniq_session_timestamp ON locations(session_id, recorded_at);

-- 2) Fast Route Reconstruction
CREATE INDEX idx_locations_session_recorded_at ON locations(session_id, recorded_at ASC);

-- 3) (Future) Analytics Expansion
CREATE INDEX idx_locations_tenant_search ON locations(organization_id, user_id, recorded_at DESC);

Strategy for Scale:

Partition by Range (Time): Transition the locations table to a PostgreSQL partitioned table grouping by recorded_at (e.g., month-by-month partitions).

Phase 5 — Per-User Rate Limiting & Ingestion Telemetry

Overview

Phase 5 upgraded the location ingestion endpoints from IP-based rate limiting to per-user JWT-sub-based rate limiting, and added latency telemetry and duplicate suppression metrics to the service layer.

5.1 — Per-User Rate Limiting

File: src/modules/locations/locations.routes.ts

Both POST /locations and POST /locations/batch are protected by a custom keyGenerator that extracts the JWT sub directly from the Authorization header during the fast onRequest phase (before the JWT plugin runs):

keyGenerator: (req: FastifyRequest) => {
  const auth = req.headers.authorization;
  if (auth && auth.startsWith("Bearer ")) {
    try {
      const base64Url = auth.split(".")[1];
      if (!base64Url) return req.ip;
      const payload = JSON.parse(
        Buffer.from(base64Url.replace(/-/g, "+").replace(/_/g, "/"), "base64").toString()
      ) as { sub?: string };
      return payload.sub ?? req.ip;
    } catch {
      return req.ip;
    }
  }
  return req.ip;
}

Why JWT sub instead of IP:

Approach	Problem
Per-IP	Employees behind a corporate NAT share one IP → one bad actor can block the whole team
Per-sub	Each employee identity is rate-limited independently — fairer and harder to abuse

Limit: 10 requests per 10 seconds per user. Falls back to req.ip if the token cannot be decoded (e.g. malformed header).

5.2 — Ingestion Telemetry

File: src/modules/locations/locations.service.ts

Two observability additions to both the single-insert and batch-insert paths:

Latency timing via performance.now():

const start = performance.now();
// ... repository call ...
const latencyMs = performance.now() - start;
request.log.info({ latencyMs, inserted }, "location insert completed");

Duplicate suppression counter (batch only):

const duplicatesSuppressed = points.length - inserted;
request.log.info(
  { intended: points.length, inserted, duplicatesSuppressed },
  "location batch insert completed",
);

Because the DB-layer upsert uses { ignoreDuplicates: true }, the number of rows actually written (inserted) can be less than the payload size (points.length). Logging the difference gives operators a signal that a mobile client is retrying stale batches.

Files Changed

File	Change
`src/modules/locations/locations.routes.ts`	Added JWT-sub `keyGenerator` to both ingestion routes; `FastifyRequest` type imported
`src/modules/locations/locations.service.ts`	Added `performance.now()` timing; batch service logs `duplicatesSuppressed`

Verification Results

Check	Result
`npx tsc --noEmit`	✅ Zero errors
Per-user limit enforced	JWT sub extracted from `Authorization` header; falls back to IP
Latency logged	`latencyMs` in every single-insert log line
Duplicate metrics	`duplicatesSuppressed` in every batch-insert log line

Phase 6 — Distance Engine & Session Summary

Architecture Overview

Introduced a computational engine designed to passively or actively calculate Haversine distances based on an employee's location pings throughout their attendance_session. The summaries are stored in a new session_summaries table.

Schema: `session_summaries`

Column	Type	Description
`session_id`	uuid (PK)	Links directly to `attendance_sessions`
`organization_id`	uuid	Tenant Isolation Key
`user_id`	uuid	Employee ID
`total_distance_meters`	double precision (float)	Cumulative calculated distance
`total_points`	integer	Total GPS ticks ingested
`duration_seconds`	integer	`check_out - check_in`
`updated_at`	timestamptz	Last recalculated timestamp

Endpoints

Method	Path	Auth	Description
POST	`/attendance/check-out`	JWT	Existing endpoint; now automatically triggers the Distance Engine.
POST	`/attendance/:sessionId/recalculate`	JWT	Explicitly recalculates distance if delayed offline points are synced.

Performance Considerations & Idempotency

O(1) Memory Streaming: A user can log upwards of 30,000 GPS points in a single 12-hour factory shift. Instead of crashing the Node.js process by pulling all 30k generic rows into RAM at once, the Distance Engine utilizes a strictly chunked streaming architecture.
- The repository's findPointsForDistancePaginated method fetches exactly 1,000 .select("latitude, longitude, recorded_at") lightweight objects per network trip.
- The calculation loop accurately tracks the absolute last point of the previousChunk to securely calculate the bridge distance to the first point of the currentChunk without disconnecting the route line mathematically.
- This allows infinite scalability. The engine runs in strict O(1) memory space, rendering memory leaks mathematically impossible regardless of session duration.
Hardware-Friendly Math: Distance is parsed cumulatively using the native Haversine formula calculation over sequential point pairs (p[i] against p[i+1]).
Telemetry Execution Timer: The entire stream operation tracks executionTimeMs via Node's performance.now() in the service layer, writing total execution durations to Pino logs for immediate Datadog observability.
Idempotency via Upsert: Because calculating distances mathematically resets the session_summaries dataset on conflict, calling the explicitly exposed recalculate reliably regenerates the absolute ground truth—safely overwriting legacy computations.

Phase 7 — Asynchronous Background Workers (Decoupled Compute)

Architecture Overview

Calculating rigorous physical distance on dense geometric location arrays—especially across chunks—takes noticeable CPU cycles (~50ms - 400ms). To ensure the primary public API remains perfectly responsive to the mobile app, the POST /attendance/check-out route has been entirely decoupled from the actual distance computation layer.

How it Works

Check-out: The user calls the /check-out API. The database successfully logs the check_out_time to close their attendance session.
Instant Return: The endpoint instantly fires the session uuid into an isolated Node.js Worker-Queue Array (export const queue), and responds with an immediate 200 OK success: true to unblock the mobile UI.
Background Worker: src/workers/queue.ts loops indefinitely on an asynchronous timeline outside the immediate HTTP request lifecycle. It plucks pending keys off the queue, generates mock system requests to bypass normal session requirements, and mathematically crunches the dense Haversine Streaming algorithms asynchronously.
Active Set Guard: To avoid overlapping recalculation scenarios (e.g. queue processing vs random manual recalculation triggers), an external Set<string> tracks the currently executing computation jobs, throwing instant 409 Conflict rejections if a client manually tries to recalculate a session that the worker is simultaneously processing.

Architectural Risks & Limitations (MVP Scope)

While this in-memory queue decouples latency from the API lifecycle, it must be acknowledged that it introduces specific limitations addressed in future production stages:

Main Event Loop Blocking: The asynchronous queue does not rely on worker_threads or true parallel child_process computing. It is purely asynchronous relative to HTTP. The heavy Haversine computation loop still utilizes the primary single-threaded Node.js event loop, which means intensive, sustained execution over millions of iterations can temporarily starve parallel I/O requests.
In-Memory Volatility: The queue (export const queue: string[] = []) is non-durable. In the result of a catastrophic SIGKILL or server restart, all queued un-crunched check-outs are destroyed.
Horizontal Scaling Limits: Deploying multiple backend instances (e.g., via AWS or Vercel edge nodes) spawns multiple independent memory pools. They do not share state, risking race conditions and potentially duplicating recalculations across separated cluster deployments. This necessitates an external durable state layer (e.g., Redis via BullMQ) at true enterprise scale.

Phase 7.5 — Crash Recovery & Self-Healing

Architecture Overview

Because the MVP asynchronous distance engine queue resides entirely in volatile memory, a hard backend server crash (e.g. out-of-memory, SIGKILL, or simple deploy restart) will immediately destroy all pending computations for employees that checked out precisely during the outage window.

To guarantee Eventual Consistency, a self-healing bootstrap daemon was added to the app.ts initialization lifecycle.

Service-Role Table Scan: When the Node environment boots, it immediately bypasses Tenant RLS via the Supabase Service Key to query a highly optimized Left-Join across all attendance_sessions and session_summaries.
Identifying Orphans: It isolates any session that is definitively closed (check_out_at IS NOT NULL), but either lacks a corresponding mathematically generated session_summaries row, or has a session_summaries.updated_at timestamp chronologically older than the check_out_at boundary (meaning a generic mid-session recalculation fired, but the final Check-Out generation dropped).
Queue Repopulation: Before the Fastify server formally accepts new port traffic, all orphaned session_id strings are automatically intercepted and injected back into the src/workers/queue.ts asynchronous memory loop.
Collision Avoidance: If an admin manually clicked "Recalculate Session" exactly while the server was booting, the worker respects the Set<string> actively processing tracker to ignore duplicative queue stacking.

This ensures no employee attendance distance metric is ever permanently stranded.

Phase 8 — Expense Module & Architecture Cleanup

Part 1 — Domain Layer Removal

The src/domain/ directory contained five empty placeholder folders (attendance/, expense/, location/, organization/, user/) from the initial scaffold. No code referenced them. They have been permanently deleted.

Architectural decision: FieldTrack 2.0 standardizes on a strict Layered Architecture (routes → controller → service → repository) co-located inside src/modules/. DDD-style domain objects are not introduced. This keeps each module self-contained and avoids premature abstraction.

Part 2 — Secured `/internal/metrics`

Prior state: GET /internal/metrics was completely unauthenticated — any internet client that reached the server could query operational telemetry.

Fix applied in src/routes/internal.ts:

app.get(
  "/internal/metrics",
  {
    preHandler: [authenticate, requireRole("ADMIN")],
  },
  async (_request, reply) => { ... }
);

JWT authentication (authenticate) runs first — unsigned or expired tokens receive a 401.
Role guard (requireRole("ADMIN")) runs second — valid EMPLOYEE tokens receive a 403.
No IP filtering or allowlist — identity is enforced by cryptographic token, not network topology.
EMPLOYEE role cannot access metrics under any circumstances.

Part 3 — Expense Module

Architecture: Route → Controller → Service → Repository

flowchart LR
    A["Client"] --> B["expenses.routes.ts"]
    B -->|"auth + role guard"| C["expenses.controller.ts"]
    C --> D["expenses.service.ts"]
    D -->|"business rules"| E["expenses.repository.ts"]
    E -->|"enforceTenant()"| F["Supabase"]

Files Created

File	Layer	Purpose
`expenses.schema.ts`	Types	DB row type, Zod body schemas, pagination schema, response interfaces
`expenses.repository.ts`	Repository	All Supabase queries — SELECT/UPDATE scoped via `enforceTenant()`
`expenses.service.ts`	Service	Business rules, structured event logs (`expense_created`, `expense_approved`, `expense_rejected`)
`expenses.controller.ts`	Controller	Zod validation, service delegation, `{ success, data }` shape
`expenses.routes.ts`	Routes	4 endpoints with auth middleware, role guards, rate limiting on creation

Database Schema

CREATE TABLE expenses (
  id               uuid PRIMARY KEY DEFAULT gen_random_uuid(),
  organization_id  uuid        NOT NULL,
  user_id          uuid        NOT NULL,
  amount           numeric     NOT NULL CHECK (amount > 0),
  description      text        NOT NULL,
  status           text        NOT NULL DEFAULT 'PENDING'
                               CHECK (status IN ('PENDING', 'APPROVED', 'REJECTED')),
  receipt_url      text,
  created_at       timestamptz NOT NULL DEFAULT now(),
  updated_at       timestamptz NOT NULL DEFAULT now()
);

Endpoints

Method	Path	Auth	Description
`POST`	`/expenses`	JWT + EMPLOYEE	Create expense (status forced to `PENDING`). Rate limited: 10/min per user.
`GET`	`/expenses/my`	JWT + EMPLOYEE	Own expenses, paginated (`page`, `limit`)
`GET`	`/admin/expenses`	JWT + ADMIN	All org expenses, paginated
`PATCH`	`/admin/expenses/:id`	JWT + ADMIN	Approve or reject a `PENDING` expense

Business Rules

EMPLOYEE can only create and view their own expenses. The service always sets status = PENDING on creation — the body cannot override this.
EMPLOYEE cannot modify an expense after creation. There is no update endpoint for employees.
ADMIN can view all org expenses scoped to their organization via GET /admin/expenses.
ADMIN can only transition PENDING → APPROVED or PENDING → REJECTED. The service rejects any action on an already-actioned expense with 400 Bad Request, preventing double-processing.
ADMIN cannot touch other organizations expenses. All repository calls use enforceTenant(), which appends .eq("organization_id", request.organizationId).

Zod Validation Rules

Field	Rule
`amount`	Required, `number`, must be `> 0`
`description`	Required, `string`, min 3 chars, max 500 chars
`receipt_url`	Optional, must be a valid URL when provided
`status` (PATCH)	Required, must be `APPROVED` or `REJECTED`
`page` / `limit`	Coerced integers; `page >= 1`, `1 <= limit <= 100`

Tenant Isolation

All SELECT and UPDATE paths pass through enforceTenant():

const baseQuery = supabase.from("expenses").select("*").eq("id", expenseId);
const { data, error } = await enforceTenant(request, baseQuery).single();

enforceTenant() appends .eq("organization_id", request.organizationId) before the terminal operation. INSERTs explicitly set organization_id: request.organizationId — no enforceTenant() needed for writes. This pattern is consistent across all modules.

Structured Log Events

Event tag	Trigger	Fields logged
`expense_created`	Successful `POST /expenses`	`expenseId`, `userId`, `organizationId`, `amount`
`expense_approved`	`PATCH` with `status: APPROVED`	`expenseId`, `userId`, `adminId`, `organizationId`, `amount`, `status`
`expense_rejected`	`PATCH` with `status: REJECTED`	`expenseId`, `userId`, `adminId`, `organizationId`, `amount`, `status`

Rate Limiting

POST /expenses is rate-limited at 10 requests per 60 seconds per user identity. The keyGenerator decodes the JWT sub directly from the Authorization header (same pattern as attendance.routes.ts and locations.routes.ts) so the limit is per-identity, not per-IP. Key format: expense-create:<sub>.

Index Strategy

-- 1) Fast employee self-service read (most common path)
CREATE INDEX idx_expenses_user_created_at
  ON expenses(user_id, created_at DESC);

-- 2) Admin org-wide paginated listing, newest-first
CREATE INDEX idx_expenses_org_created_at
  ON expenses(organization_id, created_at DESC);

-- 3) Analytics and status-based filtering per org
CREATE INDEX idx_expenses_org_status
  ON expenses(organization_id, status);

Example curl Requests

# Create an expense (EMPLOYEE)
curl -X POST http://localhost:3000/expenses \
  -H "Authorization: Bearer <EMPLOYEE_JWT>" \
  -H "Content-Type: application/json" \
  -d '{"amount": 49.99, "description": "Taxi to client site", "receipt_url": "https://cdn.example.com/receipt.jpg"}'

# View own expenses (EMPLOYEE, paginated)
curl "http://localhost:3000/expenses/my?page=1&limit=20" \
  -H "Authorization: Bearer <EMPLOYEE_JWT>"

# View all org expenses (ADMIN)
curl "http://localhost:3000/admin/expenses?page=1&limit=50" \
  -H "Authorization: Bearer <ADMIN_JWT>"

# Approve an expense (ADMIN)
curl -X PATCH "http://localhost:3000/admin/expenses/<EXPENSE_UUID>" \
  -H "Authorization: Bearer <ADMIN_JWT>" \
  -H "Content-Type: application/json" \
  -d '{"status": "APPROVED"}'

# Reject an expense (ADMIN)
curl -X PATCH "http://localhost:3000/admin/expenses/<EXPENSE_UUID>" \
  -H "Authorization: Bearer <ADMIN_JWT>" \
  -H "Content-Type: application/json" \
  -d '{"status": "REJECTED"}'

# Query secured metrics (ADMIN only — was previously public)
curl http://localhost:3000/internal/metrics \
  -H "Authorization: Bearer <ADMIN_JWT>"

Verification Results

Check	Result
`npx tsc --noEmit`	Zero errors
Domain layer (`src/domain/`) removed	Confirmed — no remaining imports
`/internal/metrics` secured	`authenticate` + `requireRole("ADMIN")` applied
Expense module files	5 files created in `src/modules/expenses/`
Routes registered in `routes/index.ts`	`expensesRoutes` registered

Phase 9 — Admin Analytics Layer

Architecture: Route → Controller → Service → Repository

flowchart LR
    A["ADMIN Client"] --> B["analytics.routes.ts"]
    B -->|"authenticate + requireRole(ADMIN)"| C["analytics.controller.ts"]
    C --> D["analytics.service.ts"]
    D -->|"two-query pattern"| E["analytics.repository.ts"]
    E --> F1["attendance_sessions"]
    E --> F2["session_summaries"]
    E --> F3["expenses"]

Files Created

File	Layer	Purpose
`analytics.schema.ts`	Types	Zod query param schemas, response data types, internal row interfaces
`analytics.repository.ts`	Repository	Minimal-select DB queries; all scoped via `enforceTenant()`
`analytics.service.ts`	Service	Aggregation logic, date validation, grouping by user_id
`analytics.controller.ts`	Controller	Zod parsing, service delegation, `{ success, data }` response shape
`analytics.routes.ts`	Routes	3 endpoints; all require `authenticate` + `requireRole("ADMIN")`

Endpoints

Method	Path	Auth	Description
`GET`	`/admin/org-summary`	JWT + ADMIN	Org-wide session/expense aggregate
`GET`	`/admin/user-summary`	JWT + ADMIN	Per-user session/expense aggregate
`GET`	`/admin/top-performers`	JWT + ADMIN	Ranked leaderboard by metric

All three endpoints accept optional from and to ISO-8601 date query parameters. If both are provided and from > to, the service throws 400 Bad Request.

Endpoint 1 — GET /admin/org-summary

Query params: from (optional ISO-8601), to (optional ISO-8601)

Response:

{
  "success": true,
  "data": {
    "totalSessions": 142,
    "totalDistanceMeters": 87432.5,
    "totalDurationSeconds": 312840,
    "totalExpenses": 31,
    "approvedExpenseAmount": 1249.75,
    "rejectedExpenseAmount": 89.99,
    "activeUsersCount": 18
  }
}

Aggregation strategy:

Query attendance_sessions for {id, user_id} within date range — org-scoped via enforceTenant().
Query session_summaries for those session IDs — org double-checked via enforceTenant().
Accumulate total_distance_meters and duration_seconds; collect distinct user_id into a Set.
Query expenses for {amount, status} within same date range.
Aggregate expense counts and totals by status in a single pass.

Why session_summaries instead of attendance_sessions + locations:
session_summaries contains one pre-computed row per closed session. Reading distance and duration from it avoids scanning the locations table which can hold 30,000+ GPS points per session. This makes org-level aggregation O(sessions) instead of O(GPS points).

Endpoint 2 — GET /admin/user-summary

Query params: userId (UUID, required), from (optional), to (optional)

Response:

{
  "success": true,
  "data": {
    "sessionsCount": 12,
    "totalDistanceMeters": 7821.3,
    "totalDurationSeconds": 28800,
    "totalExpenses": 4,
    "approvedExpenseAmount": 312.50,
    "averageDistancePerSession": 651.78,
    "averageSessionDurationSeconds": 2400
  }
}

User validation:
Before running any aggregation the service calls checkUserHasSessionsInOrg() — a lightweight .select("id").limit(1) on attendance_sessions with user_id + enforceTenant(). If no session exists for this user in the org, 404 Not Found is returned. This distinguishes "user not in this org" from "user exists but has zero sessions in this date range."

Averages:
averageDistancePerSession and averageSessionDurationSeconds are computed in the service layer. Both return 0 when sessionsCount === 0 to avoid division-by-zero.

Endpoint 3 — GET /admin/top-performers

Query params: metric (required: distance | duration | sessions), from (optional), to (optional), limit (1–50, default 10)

Response (metric=distance):

{
  "success": true,
  "data": [
    { "userId": "uuid-1", "totalDistanceMeters": 12340.5 },
    { "userId": "uuid-2", "totalDistanceMeters": 9876.0 }
  ]
}

Only the relevant metric field is included in each entry; unused metric fields are omitted to keep responses minimal.

Aggregation strategy:

Same two-query pattern: resolve session IDs, then fetch session_summaries rows.
Group by user_id in a single O(n) pass using a Map. Each entry accumulates totalDistanceMeters, totalDurationSeconds, and sessionsCount.
Sort entries descending by the chosen metric.
Slice to limit and shape output (only the sorted-by field included per entry).

metric enum validation:
Zod validates metric against ["distance", "duration", "sessions"]. Any other value returns 400 Bad Request before the DB is touched.

Aggregation Strategy and Performance

Two-Query Pattern

All session-based analytics use a consistent two-query approach:

Query 1: attendance_sessions
  SELECT id, user_id
  WHERE organization_id = :orgId
    AND check_in_at >= :from
    AND check_in_at <= :to

Query 2: session_summaries
  SELECT user_id, total_distance_meters, duration_seconds
  WHERE session_id IN (:sessionIds)
    AND organization_id = :orgId   ← defense-in-depth via enforceTenant()

This avoids:

Raw SQL joins
N+1 query patterns
Loading raw GPS location data
Full-table scans (when indexes are in place)

Why Not Direct session_summaries Scan

PostgREST (Supabase's REST interface) does not expose SQL aggregate functions (SUM, COUNT DISTINCT, GROUP BY) via the standard supabase-js API without raw SQL. Rather than using supabase.rpc() (which requires stored procedures), all aggregation is performed in application memory on pre-filtered, minimal-column result sets.

This is safe and efficient because:

session_summaries rows are pre-aggregated (one row per closed session)
Only 2 numeric columns + user_id are fetched per row (~40 bytes)
Typical date-range queries for 1–3 months return hundreds to low-thousands of rows

Tenant Isolation

Every repository method calls enforceTenant() which appends .eq("organization_id", request.organizationId) before the terminal operation. For the two-query pattern, both queries are independently enforced:

attendance_sessions query: scoped by organization_id
session_summaries query: double-scoped by organization_id in addition to the session_id IN (...) filter — an admin from org A cannot resolve session IDs from org B because the first query itself is org-locked

Zod Validation Summary

Parameter	Rule
`from`	Optional, must be ISO-8601 with timezone offset when provided
`to`	Optional, must be ISO-8601 with timezone offset when provided
`from` + `to`	When both present: `from` must not be later than `to` (service-layer check)
`userId`	Required for user-summary; must be a valid UUID
`metric`	Required for top-performers; must be `distance`, `duration`, or `sessions`
`limit`	Optional; coerced integer, 1–50, default 10

Index Dependencies

The analytics layer relies on the following indexes for efficient execution. These should be created in the database before deploying Phase 9:

-- Range scan for session list resolution
-- Used by: org-summary, user-summary, top-performers (first query)
CREATE INDEX idx_attendance_sessions_org_checkin
  ON attendance_sessions(organization_id, check_in_at DESC);

-- User-scoped range scan
-- Used by: user-summary (first query)
CREATE INDEX idx_attendance_sessions_user_checkin
  ON attendance_sessions(user_id, organization_id, check_in_at DESC);

-- IN-list lookup from resolved session IDs
-- Used by: all three endpoints (second query)
CREATE INDEX idx_session_summaries_session_org
  ON session_summaries(session_id, organization_id);

-- Expense range scan (already recommended in Phase 8; listed here for completeness)
CREATE INDEX idx_expenses_org_created_at
  ON expenses(organization_id, created_at DESC);

-- User-scoped expense scan
CREATE INDEX idx_expenses_user_org
  ON expenses(user_id, organization_id, created_at DESC);

Example curl Requests

# Org summary — last 30 days
curl "http://localhost:3000/admin/org-summary?from=2026-02-01T00:00:00Z&to=2026-03-03T23:59:59Z" \
  -H "Authorization: Bearer <ADMIN_JWT>"

# Org summary — all time (no date filter)
curl "http://localhost:3000/admin/org-summary" \
  -H "Authorization: Bearer <ADMIN_JWT>"

# User summary
curl "http://localhost:3000/admin/user-summary?userId=9b1deb4d-3b7d-4bad-9bdd-2b0d7b3dcb6d&from=2026-02-01T00:00:00Z&to=2026-03-03T23:59:59Z" \
  -H "Authorization: Bearer <ADMIN_JWT>"

# Top 5 by distance
curl "http://localhost:3000/admin/top-performers?metric=distance&limit=5&from=2026-02-01T00:00:00Z" \
  -H "Authorization: Bearer <ADMIN_JWT>"

# Top 10 by session count (default limit)
curl "http://localhost:3000/admin/top-performers?metric=sessions" \
  -H "Authorization: Bearer <ADMIN_JWT>"

# Invalid date range — returns 400
curl "http://localhost:3000/admin/org-summary?from=2026-03-01T00:00:00Z&to=2026-02-01T00:00:00Z" \
  -H "Authorization: Bearer <ADMIN_JWT>"

Verification Results

Check	Result
`npx tsc --noEmit`	Zero errors
All endpoints require ADMIN	`authenticate` + `requireRole("ADMIN")` on all routes
No `select("*")` in analytics	Only named columns fetched
No raw SQL	Supabase JS client only
`from > to` guard	`BadRequestError` thrown in service before any DB call
`userId` validation	`checkUserHasSessionsInOrg()` before aggregation
Routes registered	`analyticsRoutes` registered in `routes/index.ts`

Phase 10 — Production Hardening & Enterprise Correctness

Overview

Phase 10 transforms FieldTrack 2.0 from a highly functional single-instance backend into a production-grade, horizontally scalable service. Four pillars are addressed: durable job processing, defence-in-depth database access control, end-to-end request tracing, and HTTP-layer security hardening.

10.1 — Redis + BullMQ Durable Queue

Why In-Memory Queue Was Replaced

The Phase 7 in-memory queue had three structural limits:

Problem	Impact
Volatile memory	All pending jobs lost on process restart, deploy, or OOM kill
Single-process bound	Cannot scale horizontally — multiple pods would run isolated queues
Manual retry logic	Failed jobs were silently dropped; no backoff, no retained failure record

BullMQ Architecture

┌─────────────────────────────────────────────────────────────────┐
│  HTTP Request Lifecycle                                          │
│                                                                  │
│  POST /attendance/check-out                                      │
│       │                                                          │
│       ▼                                                          │
│  attendanceService.checkOut()                                    │
│       │                                                          │
│       │  enqueueDistanceJob(sessionId)  ─── fire & forget        │
│       │         │                                                │
│       │         ▼ (async, non-blocking)                          │
│       │   BullMQ Queue ──────────────────► Redis (persisted)     │
│       │                                       [jobId=sessionId]  │
│       │                                                          │
│       ▼                                                          │
│  200 OK (instant)                                                │
└─────────────────────────────────────────────────────────────────┘

┌─────────────────────────────────────────────────────────────────┐
│  Background Worker Lifecycle                                     │
│                                                                  │
│  BullMQ Worker polls Redis queue                                 │
│       │                                                          │
│       ▼                                                          │
│  Job: { sessionId }                                              │
│       │                                                          │
│       ▼                                                          │
│  sessionSummaryService.calculateAndSaveSystem(app, sessionId)    │
│       │                                                          │
│       ├── success → metrics.recordRecalculationTime()            │
│       │            log: { jobId, sessionId, executionTimeMs }    │
│       │                                                          │
│       └── failure → BullMQ retries with exponential backoff      │
│                     (attempts: 5 → delays: 1s, 2s, 4s, 8s, 16s) │
│                     Failed jobs retained in Redis (removeOnFail:false)
└─────────────────────────────────────────────────────────────────┘

Idempotency Guarantee

enqueueDistanceJob() passes { jobId: sessionId } to BullMQ. BullMQ silently ignores a duplicate add() call if a job with the same jobId already exists in the queue. This replaces the Phase 7 queuedSet: Set<string> deduplication without any in-memory state.

Files Changed / Created

File	Action	Notes
`src/config/redis.ts`	NEW	Parses `REDIS_URL` into BullMQ connection options; handles `rediss://` TLS
`src/workers/distance.queue.ts`	NEW	BullMQ `Queue` definition + `enqueueDistanceJob()` + `getQueueDepth()`
`src/workers/distance.worker.ts`	NEW	BullMQ `Worker` processor + `startDistanceWorker()` + `performStartupRecovery()`
`src/workers/queue.ts`	DELETED	Phase 7 in-memory queue removed
`src/modules/attendance/attendance.service.ts`	MODIFIED	`enqueueDistanceRecalculation` → `enqueueDistanceJob` (fire-and-forget)
`src/modules/session_summary/session_summary.controller.ts`	MODIFIED	Removed `processingTracker` import (BullMQ handles dedup via jobId)
`src/routes/internal.ts`	MODIFIED	`getQueueDepth` now imported from `distance.queue.ts`; awaited (async)
`src/app.ts`	MODIFIED	`startDistanceWorker` imported from `distance.worker.ts`

Job Configuration

Setting	Value	Rationale
`attempts`	5	Tolerate transient DB/network failures
`backoff.type`	`exponential`	Avoid thundering herd on recovery
`backoff.delay`	1000 ms	1s → 2s → 4s → 8s → 16s
`removeOnComplete`	true	Completed jobs need no retention
`removeOnFail`	false	Keep failed jobs for operator inspection
`concurrency`	1	CPU-bound Haversine loop; one job at a time

Crash Recovery (Phase 7.5 Preserved)

performStartupRecovery() is now in distance.worker.ts. It scans for orphaned sessions and re-enqueues them via enqueueDistanceJob() (backed by Redis) instead of the old in-memory push. Jobs survive a second crash during recovery because they are already in Redis before the process exits.

10.2 — Supabase Client Separation (RLS Defence-in-Depth)

Prior State

The entire backend used a single supabaseServiceClient (service role key) for every database operation. This bypassed PostgreSQL Row Level Security (RLS) globally — a correct approach for backend systems where RLS is redundant when code enforces tenant isolation — but offered no second layer of protection.

Phase 10 Strategy

Two named clients are now exported from src/config/supabase.ts:

Client	Key Used	RLS	Usage
`supabaseAnonClient`	`SUPABASE_ANON_KEY`	Enforced	All normal HTTP request handlers
`supabaseServiceClient`	`SUPABASE_SERVICE_ROLE_KEY`	Bypassed	System paths only (listed below)

Service client usage is restricted to:

attendance.repository.ts → findSessionsNeedingRecalculation() — crash recovery bootstrap scan across all tenants
session_summary.repository.ts — worker writes (no user JWT available at write time)
session_summary.service.ts — direct session lookup in calculateAndSaveSystem() (worker path)

Anon client is used in:

attendance.repository.ts (all request-path methods)
locations.repository.ts
expenses.repository.ts
analytics.repository.ts

Why Not Remove enforceTenant() With RLS?

enforceTenant() is retained alongside the anon client for defence-in-depth:

RLS policy misconfiguration — if a RLS policy is accidentally dropped or misconfigured in Supabase, enforceTenant() still filters at the application layer
Complex queries — some joins or subqueries may not be covered by RLS policies in all Supabase versions
Worker paths — worker paths explicitly use the service client (no JWT) and rely entirely on enforceTenant() for isolation

The combination (supabaseAnonClient + enforceTenant()) provides two independent layers; either layer failing alone does not expose cross-tenant data.

10.3 — Request Correlation & Observability Upgrade

Request ID Generation

Fastify's built-in request ID support is enabled in app.ts:

const app = Fastify({
  requestIdHeader: "x-request-id",  // Accept client-provided ID
  genReqId: () => randomUUID(),     // Generate UUID if not provided
});

Every request gets a UUID attached to request.id. The ID is:

Injected into Pino's log context automatically (Fastify wraps the logger with request-scoped bindings including reqId)
Returned in every response header as x-request-id (via onSend hook)
Included in all error response bodies as requestId

Error Response Shape (Phase 10)

All error responses across every controller now follow a consistent shape:

{
  "success": false,
  "error": "Human-readable error message",
  "requestId": "550e8400-e29b-41d4-a716-446655440000"
}

This applies to:

Zod validation failures (400)
AppError subclasses (400, 401, 403, 404)
Unexpected 500 errors

Clients and monitoring tools can correlate error reports to specific log lines using the requestId without manually parsing log files.

Worker Log Correlation

The BullMQ worker logs include jobId and sessionId on every state transition:

{ "level": "info", "jobId": "uuid", "sessionId": "uuid", "executionTimeMs": 142, "msg": "Distance worker: job completed successfully" }
{ "level": "error", "jobId": "uuid", "sessionId": "uuid", "executionTimeMs": 23, "error": "...", "msg": "Distance worker: job failed" }

10.4 — HTTP Security Hardening

Plugins Registered

Plugin	Purpose
`@fastify/helmet`	Sets security headers: `Strict-Transport-Security`, `X-Frame-Options`, `X-Content-Type-Options`, `Content-Security-Policy`
`@fastify/compress`	Gzip/deflate/brotli response compression; reduces bandwidth on JSON-heavy analytics responses
`@fastify/cors`	Restricts `Origin` header to the `ALLOWED_ORIGINS` list; blocks cross-origin requests from unlisted domains

Fastify Server Options

const app = Fastify({
  bodyLimit: 1_000_000,     // 1 MB — prevents large body DoS attacks
  connectionTimeout: 5_000, // 5 s — drops slow TCP connects
  keepAliveTimeout: 72_000, // 72 s — tuned for AWS ALB / Nginx upstream
});

CORS Configuration

ALLOWED_ORIGINS is a comma-separated list of permitted origins:

ALLOWED_ORIGINS=https://app.fieldtrack.io,https://admin.fieldtrack.io

If ALLOWED_ORIGINS is empty, CORS is disabled (all cross-origin requests blocked), which is appropriate for API-only deployments accessed from a backend or mobile app without a browser.

10.5 — Environment Variables Required

The following environment variables must be present for Phase 10 to boot:

Variable	Phase Added	Required	Description
`SUPABASE_URL`	Phase 0	✅	Supabase project URL
`SUPABASE_SERVICE_ROLE_KEY`	Phase 0	✅	Supabase service role key
`SUPABASE_ANON_KEY`	Phase 10	✅	Supabase anon/public key
`SUPABASE_JWT_SECRET`	Phase 1	✅	Supabase JWT signing secret
`REDIS_URL`	Phase 10	✅	Redis connection URL (`redis://` or `rediss://`)
`ALLOWED_ORIGINS`	Phase 10	Optional	Comma-separated CORS origins
`PORT`	Phase 0	Optional	HTTP server port (default: 3000)
`NODE_ENV`	Phase 0	Optional	`development` or `production`
`MAX_QUEUE_DEPTH`	Phase 7	Optional	Max sessions per queue depth (default: 1000)
`MAX_POINTS_PER_SESSION`	Phase 7	Optional	Max GPS points per recalculation (default: 50000)
`MAX_SESSION_DURATION_HOURS`	Phase 7	Optional	Max session age for recalculation (default: 168)

Horizontal Scaling

Phase 10 removes all blockers for multi-instance deployment:

┌──────────────────────────────────────────────────────────────┐
│  Load Balancer (AWS ALB / Nginx)                              │
│       │               │                                       │
│       ▼               ▼                                       │
│  Backend Pod 1    Backend Pod 2   ...                         │
│  (Fastify)        (Fastify)                                   │
│       │               │                                       │
│       └───────┬───────┘                                       │
│               ▼                                               │
│           Supabase (PostgreSQL + RLS)                         │
│               │                                               │
│       ┌───────┴───────┐                                       │
│       ▼               ▼                                       │
│   Redis Queue     Redis Queue  ← same instance, shared state  │
│     BullMQ           BullMQ                                   │
│   Worker Pod 1   Worker Pod 2  ← jobs distributed across pods │
└──────────────────────────────────────────────────────────────┘

What enables horizontal scaling:

Concern	Phase 7 (In-Memory)	Phase 10 (Redis)
Job durability	❌ Lost on crash	✅ Persisted in Redis
Multi-pod deduplication	❌ Each pod had its own Set	✅ BullMQ jobId dedup in Redis
Worker distribution	❌ All pods duplicate work	✅ Jobs distributed across workers
Crash recovery	❌ Manual re-enqueue needed	✅ Auto-retry via BullMQ backoff

Files Changed / Created Summary

File	Action
`src/config/env.ts`	MODIFIED — Added `REDIS_URL`, `SUPABASE_ANON_KEY`, `ALLOWED_ORIGINS`
`src/config/supabase.ts`	MODIFIED — Split into `supabaseAnonClient` + `supabaseServiceClient`
`src/config/redis.ts`	NEW — Redis connection options parser
`src/workers/distance.queue.ts`	NEW — BullMQ Queue + `enqueueDistanceJob`
`src/workers/distance.worker.ts`	NEW — BullMQ Worker + crash recovery
`src/workers/queue.ts`	DELETED — In-memory queue removed
`src/app.ts`	MODIFIED — Helmet, compress, CORS, request ID, body limits, global error handler
`src/server.ts`	MODIFIED — `performStartupRecovery` imported from `distance.worker.ts`
`src/modules/attendance/attendance.service.ts`	MODIFIED — Uses `enqueueDistanceJob`
`src/modules/attendance/attendance.repository.ts`	MODIFIED — `supabaseAnonClient`; `supabaseServiceClient` for recovery scan
`src/modules/attendance/attendance.controller.ts`	MODIFIED — `requestId` in all error responses
`src/modules/locations/locations.repository.ts`	MODIFIED — `supabaseAnonClient`
`src/modules/locations/locations.controller.ts`	MODIFIED — `requestId` in all error responses
`src/modules/expenses/expenses.repository.ts`	MODIFIED — `supabaseAnonClient`
`src/modules/expenses/expenses.controller.ts`	MODIFIED — `requestId` in all error responses
`src/modules/analytics/analytics.repository.ts`	MODIFIED — `supabaseAnonClient`
`src/modules/analytics/analytics.controller.ts`	MODIFIED — `requestId` in all error responses
`src/modules/session_summary/session_summary.repository.ts`	MODIFIED — `supabaseServiceClient` (worker path)
`src/modules/session_summary/session_summary.service.ts`	MODIFIED — `supabaseServiceClient` (worker path)
`src/modules/session_summary/session_summary.controller.ts`	MODIFIED — Removed `processingTracker`; `requestId` in error responses
`src/routes/internal.ts`	MODIFIED — `getQueueDepth` from `distance.queue.ts` (now async)

Verification Results

Check	Result
`npx tsc --noEmit`	✅ Zero errors
`@fastify/helmet` registered	Security headers set on every response
`@fastify/compress` registered	Gzip/brotli enabled
`@fastify/cors` registered	Origin-restricted via `ALLOWED_ORIGINS`
`bodyLimit: 1_000_000`	1 MB request cap enforced
`genReqId` → UUID	Every request gets a unique trace ID
`x-request-id` header	Attached to every response via `onSend` hook
Error bodies include `requestId`	All controllers + global error handler updated
`supabaseAnonClient` in request handlers	✅ RLS enforced by default
`supabaseServiceClient` restricted	✅ Only recovery scan + worker writes
`queue.ts` deleted	✅ In-memory queue fully removed
`enqueueDistanceJob` (BullMQ)	Jobs stored in Redis, survive restarts
BullMQ worker starts on boot	`startDistanceWorker(app)` called in `buildApp()`
Crash recovery re-enqueues to Redis	`performStartupRecovery` in `distance.worker.ts`

Phase 11 — CI/CD Deployment Hardening

Overview

Phase 11 hardens the deployment lifecycle without touching any business logic, queue implementation, or Supabase client configuration. All changes target operational correctness: safe container shutdown, prevention of duplicate worker processes, container health observability, and a deployment audit trail.

11.1 — Graceful Shutdown

File: src/server.ts

Docker sends SIGTERM when stopping a container (docker stop, rolling deploy, ECS task replacement). Without a handler, Node.js exits immediately — BullMQ workers can leave jobs mid-flight and Redis connections are abandoned without a proper close handshake, sometimes causing delay on the next startup.

Implementation:

const shutdown = async (signal: string): Promise<void> => {
  app.log.info(`${signal} received, shutting down gracefully...`);
  await app.close();  // closes HTTP server + drains in-flight requests
  process.exit(0);
};

process.on("SIGTERM", () => void shutdown("SIGTERM"));
process.on("SIGINT",  () => void shutdown("SIGINT"));

app.close() is Fastify's built-in drain mechanism — it stops accepting new connections, waits for in-flight requests to complete, then tears down plugins in reverse registration order (including BullMQ workers registered as Fastify plugins in the future).

Both SIGTERM (Docker/orchestrator stop) and SIGINT (Ctrl-C in dev) are handled identically.

11.2 — Worker Double-Start Guard

File: src/workers/distance.worker.ts

startDistanceWorker() is called once in buildApp(). In development with tsx watch, hot-reload can re-evaluate modules without restarting the process, potentially spawning a second BullMQ Worker instance connected to the same Redis queue. Two workers competing over the same queue can cause duplicate job processing and confusing log output.

Implementation:

let workerStarted = false;

export function startDistanceWorker(app: FastifyInstance): Worker | null {
  if (workerStarted) {
    app.log.warn("startDistanceWorker called more than once — ignoring duplicate start");
    return null;
  }
  workerStarted = true;
  // ... existing worker creation
}

The module-level workerStarted flag persists for the lifetime of the Node.js process. A second call logs a warning (visible in structured logs) and returns without creating a new worker.

11.3 — Docker Healthcheck

File: Dockerfile

Without a HEALTHCHECK, Docker and orchestrators (ECS, Kubernetes, Fly.io) cannot distinguish between a container that is starting up and one that has crashed silently. CI/CD pipelines that deploy via rolling update have no signal to know when to shift traffic.

Implementation:

RUN apk add --no-cache curl

HEALTHCHECK --interval=30s --timeout=5s --start-period=10s --retries=3 \
  CMD curl -f http://localhost:3000/health || exit 1

Parameter	Value	Rationale
`--interval`	30s	Check every 30 seconds after healthy
`--timeout`	5s	Container marked unhealthy if `/health` takes > 5s
`--start-period`	10s	Grace period before first check — allows Redis connect + recovery scan
`--retries`	3	Three consecutive failures → `unhealthy` (transient errors tolerated)

The probe hits GET /health which is the existing health route — no new endpoint needed. curl -f returns exit code 22 on HTTP 4xx/5xx, which triggers the || exit 1 fallback.

curl is installed via apk add --no-cache curl since the base image (node:18-alpine) does not include it by default.

11.4 — Deployment Log Marker

File: src/server.ts

GitHub Actions injects GITHUB_SHA as an environment variable during workflow runs. Logging it at boot time creates an auditable record in structured logs:

app.log.info(
  { version: process.env["GITHUB_SHA"] ?? "manual" },
  "Server booted",
);

Example log line in production (Pino JSON):

{ "level": "info", "version": "a3f9c1d7b...", "msg": "Server booted" }

When GITHUB_SHA is absent (local dev, manual deploy), the value is "manual". This field can be indexed in Datadog, CloudWatch Logs Insights, or any structured log query to answer "which git commit is running right now?"

Files Changed

File	Change
`src/server.ts`	Added `SIGTERM`/`SIGINT` graceful shutdown handlers; added boot log marker with `GITHUB_SHA`
`src/workers/distance.worker.ts`	Added `workerStarted` flag; `startDistanceWorker` returns `Worker \| null` and is idempotent
`Dockerfile`	Added `apk add curl`; added `HEALTHCHECK` directive

Verification Results

Check	Result
`npx tsc --noEmit`	✅ Zero errors
`SIGTERM` handler	Calls `app.close()` then `process.exit(0)`
`SIGINT` handler	Same as SIGTERM — safe for local dev Ctrl-C
Worker double-start	Second call to `startDistanceWorker` returns `null` + logs warning
`HEALTHCHECK` in Dockerfile	`curl -f http://localhost:3000/health` every 30s
`curl` available in image	`apk add --no-cache curl` in production stage
Boot log marker	`{ version: GITHUB_SHA \| "manual" }` logged after listen
`host: "0.0.0.0"` binding	Confirmed unchanged — container accessible from outside

Phase 12 — Prometheus Metrics Instrumentation

Overview

Phase 12 adds a Prometheus scrape endpoint and full HTTP request instrumentation to FieldTrack 2.0. This is a pure observability addition — no business logic, no auth, no changes to existing routes. The existing /internal/metrics JSON endpoint is untouched.

Two categories of metrics are collected:

Default Node.js metrics — CPU, heap, event-loop lag, GC, libuv handles (zero application code needed)
HTTP request metrics — per-route request counts and latency histograms labelled by method, route, and status code

12.1 — Why Prometheus

The existing GET /internal/metrics endpoint returns a custom JSON snapshot of application-level counters (queue depth, recalculation timings). It is useful for human operators but cannot be scraped by Prometheus, Grafana, Datadog Agent, or any standard monitoring stack.

Prometheus exposition format is the de-facto standard for time-series metrics collection. Adding it enables:

Node.js runtime visibility — CPU usage, heap size, event-loop lag, GC duration, libuv handle counts — out of the box with zero instrumentation code
HTTP traffic visibility — request rates, error rates, and latency percentiles per route via http_requests_total and http_request_duration_seconds
Grafana dashboards — plug-and-play with the standard Node.js dashboard (ID 11159)
Alerting — heap threshold alerts, p99 latency alerts, error-rate spikes without custom code
Cloud-native compatibility — works with Prometheus Operator on Kubernetes, AWS Managed Prometheus, Grafana Cloud

12.2 — Default Node.js Metrics

Dependency

prom-client  (v15+)

prom-client is the official Prometheus client for Node.js. collectDefaultMetrics() automatically instruments the following using native Node.js APIs:

Metric	Source
`process_cpu_seconds_total`	`process.cpuUsage()`
`process_resident_memory_bytes`	`process.memoryUsage().rss`
`nodejs_heap_size_total_bytes`	V8 heap stats
`nodejs_heap_size_used_bytes`	V8 heap stats
`nodejs_external_memory_bytes`	V8 heap stats
`nodejs_eventloop_lag_seconds`	`perf_hooks`
`nodejs_gc_duration_seconds`	`PerformanceObserver` (GC)
`nodejs_active_handles_total`	`process._getActiveHandles()`
`nodejs_active_requests_total`	`process._getActiveRequests()`

12.3 — HTTP Request Metrics

Metrics Defined

const httpRequestsTotal = new client.Counter({
  name: "http_requests_total",
  help: "Total number of HTTP requests",
  labelNames: ["method", "route", "status_code"],
  registers: [register],
});

const httpRequestDuration = new client.Histogram({
  name: "http_request_duration_seconds",
  help: "HTTP request latency in seconds",
  labelNames: ["method", "route", "status_code"],
  buckets: [0.01, 0.05, 0.1, 0.2, 0.5, 1, 2, 5],
  registers: [register],
});

Bucket rationale: The eight buckets span 10 ms → 5 s, covering the expected range for a JSON API:

0.01 — fast in-memory/cache responses
0.05–0.1 — normal Supabase queries
0.2–0.5 — complex analytics aggregations
1–5 — Haversine recalculation, slow queries, timeouts

Fastify Hooks

Hook	Action
`onRequest`	Records `process.hrtime()` into a `WeakMap<IncomingMessage, [number, number]>`
`onResponse`	Reads start time, computes elapsed seconds, calls `observe()` + `inc()`, deletes WeakMap entry

Why WeakMap instead of patching request.raw:
Attaching properties to IncomingMessage requires unsafe type casting (as unknown as ...) and pollutes the Node.js HTTP object. A WeakMap keyed on request.raw is garbage-collected automatically when the request is destroyed — no memory leaks, no type hacks.

Route label via request.routeOptions.url:
Using request.url would produce a unique label per request (e.g. /attendance/my-sessions?page=1&limit=20), causing unbounded cardinality. request.routeOptions.url returns the registered route pattern (e.g. /attendance/my-sessions), keeping cardinality bounded to the number of routes.

Self-scrape exclusion:
The onResponse hook skips route === "/metrics" to avoid recording scrape requests as application traffic.

12.4 — Full Plugin File

src/plugins/prometheus.ts

import type { FastifyPluginAsync } from "fastify";
import type { IncomingMessage } from "http";
import client from "prom-client";

const register = new client.Registry();
client.collectDefaultMetrics({ register });

const httpRequestsTotal = new client.Counter({
  name: "http_requests_total",
  help: "Total number of HTTP requests",
  labelNames: ["method", "route", "status_code"],
  registers: [register],
});

const httpRequestDuration = new client.Histogram({
  name: "http_request_duration_seconds",
  help: "HTTP request latency in seconds",
  labelNames: ["method", "route", "status_code"],
  buckets: [0.01, 0.05, 0.1, 0.2, 0.5, 1, 2, 5],
  registers: [register],
});

const timings = new WeakMap<IncomingMessage, [number, number]>();

const prometheusPlugin: FastifyPluginAsync = async (fastify) => {
  fastify.addHook("onRequest", (request, _reply, done) => {
    timings.set(request.raw, process.hrtime());
    done();
  });

  fastify.addHook("onResponse", (request, reply, done) => {
    const route = request.routeOptions?.url ?? request.url;
    if (route === "/metrics") { done(); return; }

    const start = timings.get(request.raw);
    if (start !== undefined) {
      const diff = process.hrtime(start);
      const seconds = diff[0] + diff[1] / 1e9;
      const labels = { method: request.method, route, status_code: String(reply.statusCode) };
      httpRequestDuration.labels(labels).observe(seconds);
      httpRequestsTotal.labels(labels).inc();
      timings.delete(request.raw);
    }
    done();
  });

  fastify.get("/metrics", async (_request, reply) => {
    await reply
      .header("Content-Type", register.contentType)
      .send(await register.metrics());
  });
};

export default prometheusPlugin;

Registration in `src/app.ts`

import prometheusPlugin from "./plugins/prometheus.js";

// Registered before registerJwt() — route sits outside auth scope
await app.register(prometheusPlugin);

12.5 — Endpoint Comparison

	`GET /metrics`	`GET /internal/metrics`
Format	Prometheus text (exposition)	Custom JSON
Auth	None	JWT + ADMIN
Consumer	Prometheus scraper, Grafana Agent	Human operator, internal dashboards
Content-Type	`text/plain; version=0.0.4`	`application/json`
Data	Node.js runtime + HTTP request stats	App-level counters (queue depth, recalculation timings)
Phase introduced	Phase 12	Phase 8

Files Changed

File	Action
`src/plugins/prometheus.ts`	NEW — isolated registry, default metrics, HTTP counter + histogram, Fastify hooks, `/metrics` route
`src/app.ts`	MODIFIED — import + `await app.register(prometheusPlugin)` before JWT
`package.json`	MODIFIED — `prom-client` added to dependencies

Example Output

# HELP process_cpu_user_seconds_total Total user CPU time spent in seconds.
# TYPE process_cpu_user_seconds_total counter
process_cpu_user_seconds_total 0.234

# HELP nodejs_heap_size_used_bytes Process heap size used from Node.js in bytes.
# TYPE nodejs_heap_size_used_bytes gauge
nodejs_heap_size_used_bytes 24756224

# HELP nodejs_eventloop_lag_seconds Lag of event loop in seconds.
# TYPE nodejs_eventloop_lag_seconds gauge
nodejs_eventloop_lag_seconds 0.000312

# HELP http_requests_total Total number of HTTP requests
# TYPE http_requests_total counter
http_requests_total{method="POST",route="/attendance/check-out",status_code="200"} 47
http_requests_total{method="POST",route="/locations/batch",status_code="200"} 312
http_requests_total{method="GET",route="/attendance/my-sessions",status_code="401"} 3

# HELP http_request_duration_seconds HTTP request latency in seconds
# TYPE http_request_duration_seconds histogram
http_request_duration_seconds_bucket{le="0.01",method="GET",route="/health",status_code="200"} 120
http_request_duration_seconds_bucket{le="0.1",method="POST",route="/attendance/check-out",status_code="200"} 44
http_request_duration_seconds_sum{method="POST",route="/attendance/check-out",status_code="200"} 3.821
http_request_duration_seconds_count{method="POST",route="/attendance/check-out",status_code="200"} 47

Verification Results

Check	Result
`npx tsc --noEmit`	✅ Zero errors
`GET /metrics` responds	Prometheus exposition text
`Content-Type` header	`text/plain; version=0.0.4`
No auth on `/metrics`	Route registered before JWT plugin
`GET /internal/metrics` unchanged	Still requires JWT + ADMIN
Default metrics collected	CPU, heap, GC, event-loop lag, handles
Isolated registry	`new client.Registry()` — not the global singleton
`http_requests_total` counter	Labelled by method, route pattern, status code
`http_request_duration_seconds` histogram	8 buckets: 10ms → 5s
Timer storage	`WeakMap<IncomingMessage>` — no type casting, no memory leaks
Route cardinality	`routeOptions.url` (pattern) not `request.url` (full path)
Self-scrape excluded	`/metrics` route skipped in `onResponse` hook

Phase 16 — Schema Rebuild with ENUM Types

Overview

Phase 16 performed a clean database reset, replacing all TEXT columns that carried constrained values with native PostgreSQL ENUM types. TypeScript types were re-generated from the new schema to keep the type system in sync.

What Changed

Area	Before	After
`role` on `employees`	`TEXT`	`ENUM user_role ('ADMIN','EMPLOYEE')`
`status` on `expenses`	`TEXT`	`ENUM expense_status ('PENDING','APPROVED','REJECTED')`
`distance_recalculation_status` on `attendance_sessions`	`TEXT`	`ENUM distance_job_status ('pending','processing','done','failed')`
TypeScript types	Manually maintained	Auto-generated via `supabase gen types typescript --linked`

Files Created / Modified

File	Action	Purpose
`supabase/migrations/20260309000000_phase16_schema.sql`	NEW	Full schema DDL with ENUM types, all 7 tables, indexes, RLS policies
`src/types/database.ts`	REGENERATED	Supabase-generated TypeScript types (removed from `.gitignore` so Docker can build)
`src/types/db.ts`	NEW	Human-readable type aliases — `AttendanceSession`, `Expense`, `GpsLocation`, etc.
Attendance / expenses / locations / analytics schema files	UPDATED	Import row types from `db.ts` instead of long `Database["public"]["Tables"][...]["Row"]` paths

Migration Steps

supabase db reset --linked --yes
supabase gen types typescript --linked > src/types/database.ts

Phase 17 — API & Service Layer Hardening

Overview

Phase 17 hardened the entire API surface without adding new endpoints. The goals were:

Uniform response shape — every endpoint returns the same { success, data } / { success, error, requestId } envelope, built by shared helpers
Domain-specific errors — business rule violations produce typed, descriptive messages instead of generic BadRequestError
Reusable pagination — a single applyPagination() replaces four copies of identical offset arithmetic
Employee-scoped location routes — employees can only read their own GPS tracks, not any session in the org
Type safety in route config — eliminated any cast in rate-limit keyGenerator

Files Created

`src/utils/response.ts`

Provides three exports used by every controller:

// Type aliases
type SuccessResponse<T> = { success: true; data: T }
type ErrorResponse     = { success: false; error: string; requestId: string }
type ApiResponse<T>    = SuccessResponse<T> | ErrorResponse

// Builders
function ok<T>(data: T): SuccessResponse<T>
function fail(error: string, requestId: string): ErrorResponse

// Unified catch handler
function handleError(error: unknown, request, reply, context: string): void

handleError dispatch priority:

AppError subclass  →  error.statusCode (400 / 401 / 403 / 404)
ZodError           →  400, issues joined with "; "
anything else      →  500, logged with request.log.error(error, context)

Before this file existed, every controller had 4-line catch blocks duplicating the same AppError instanceof check and manual 500 send. Now every catch block is a single line.

`src/utils/pagination.ts`

const PAGINATION_DEFAULTS = { LIMIT: 50, MAX_LIMIT: 100 }

function applyPagination<T extends Rangeable>(query: T, page: number, limit: number): T
// clamps page ≥ 1, limit ∈ [1, 100]
// calls .range(offset, offset + safeLimit - 1) on the Supabase query builder

Four list queries across three repositories previously duplicated:

const offset = (page - 1) * limit;
query.range(offset, offset + limit - 1)

All four now delegate to applyPagination().

Files Modified

`src/utils/errors.ts` — Domain Error Classes

Three domain-specific error subclasses added after ForbiddenError:

Class	HTTP	Message
`EmployeeAlreadyCheckedIn`	400	"Cannot check in: you already have an active session. Check out first."
`SessionAlreadyClosed`	400	"Cannot check out: no active session found. Check in first."
`ExpenseAlreadyReviewed`	400	"Expense has already been {status}. Only PENDING expenses can be actioned."

All extend BadRequestError → AppError, so handleError picks them up automatically.

`src/modules/attendance/attendance.repository.ts`

Added findEmployeeInOrg(request, employeeId): Promise<boolean> — queries employees table with org scope + is_active = true; returns true if found
findSessionsByUser and findSessionsByOrg now use applyPagination() instead of inline offset arithmetic

`src/modules/attendance/attendance.service.ts`

checkIn now enforces two rules in order:

1. findEmployeeInOrg()  →  NotFoundError if employee doesn't belong to org
2. findOpenSession()    →  EmployeeAlreadyCheckedIn if session already open

checkOut throws SessionAlreadyClosed instead of a generic BadRequestError.

`src/modules/expenses/expenses.repository.ts`

findExpensesByUser and findExpensesByOrg use applyPagination().

`src/modules/expenses/expenses.service.ts`

updateExpenseStatus throws ExpenseAlreadyReviewed(expense.status) when the expense is not PENDING.

`src/modules/locations/locations.repository.ts`

findLocationsBySession accepts an optional employeeId?: string; when present, adds .eq("employee_id", employeeId) before enforceTenant
findPointsForDistancePaginated uses applyPagination()

`src/modules/locations/locations.service.ts`

getRoute now passes request.user.sub as the employeeId argument to findLocationsBySession, ensuring employees can only retrieve GPS tracks that belong to their own employee record — not any session in the organization.

`src/modules/locations/locations.routes.ts`

Rate-limit keyGenerator fixed:

Issue	Fix
`req: any`	Changed to `req: FastifyRequest`; `FastifyInstance` import updated to `FastifyInstance, FastifyRequest`
Potential crash on malformed JWT	Added `if (!base64Url) return req.ip;` null guard
Untyped payload	Cast as `{ sub?: string }`
`payload.sub \|\| req.ip`	Changed to `payload.sub ?? req.ip` (null-coalescing)

All 5 Controllers

Every controller replaced its manual { success: true, data } / { success: false, error, requestId } inline construction with ok() / fail() / handleError().

Before (per handler, ~8 lines):

try {
  const result = await service.method(request);
  reply.status(200).send({ success: true, data: result });
} catch (error) {
  if (error instanceof AppError) {
    reply.status(error.statusCode).send({ success: false, error: error.message, requestId: request.id });
    return;
  }
  request.log.error(error, "context");
  reply.status(500).send({ success: false, error: "Internal server error", requestId: request.id });
}

After (per handler, 4 lines):

try {
  const result = await service.method(request);
  reply.status(200).send(ok(result));
} catch (error) {
  handleError(error, request, reply, "context");
}

How It All Connects

sequenceDiagram
    participant Client
    participant Controller
    participant Service
    participant Repository
    participant DB as Supabase

    Client->>Controller: HTTP Request
    Controller->>Controller: Zod schema parse (safeParse or parse)
    alt Validation fails
        Controller-->>Client: 400 fail("Validation failed: ...", requestId)
    end
    Controller->>Service: business method(request, args)
    Service->>Repository: findEmployeeInOrg / findOpenSession / etc.
    Repository->>DB: enforceTenant() + applyPagination()
    alt Domain rule violated
        Service-->>Controller: throws EmployeeAlreadyCheckedIn | SessionAlreadyClosed | ExpenseAlreadyReviewed
        Controller-->>Client: 400 fail(domainError.message, requestId)
    end
    Service-->>Controller: typed result
    Controller-->>Client: 201/200 ok(result)

Verification

npx tsc --noEmit

Result: 0 errors across all 3 utility files, 3 repositories, 2 services, 5 controllers, and 1 route file.

Phase 13 — Production Infrastructure (Moved)

Infrastructure ownership was extracted from this API repository.

The following are now managed in the standalone infra repository:

VPS bootstrap and host setup
nginx reverse proxy configuration
Redis runtime service
monitoring stack (Prometheus, Grafana, Loki, Alertmanager, Promtail)

This API repository now focuses on application code and deployment orchestration only.

Phase 14 — Distributed Tracing, Log Correlation & Metric Exemplars

Overview

Phase 14 connected the three pillars of observability — metrics, logs, and traces — into a unified view in Grafana. Any single request can now be followed from a Prometheus data point → Loki log line → Tempo trace span in a single click.

14.1 — OpenTelemetry Tracing

File: src/tracing.ts

Must be the first import in server.ts so the SDK wraps all subsequently-loaded modules.

import { NodeSDK } from "@opentelemetry/sdk-node";
import { OTLPTraceExporter } from "@opentelemetry/exporter-trace-otlp-http";
import { getNodeAutoInstrumentations } from "@opentelemetry/auto-instrumentations-node";

// Ships traces to Grafana Tempo via OTLP HTTP
const exporter = new OTLPTraceExporter({
  url: `${env.TEMPO_ENDPOINT}/v1/traces`,
});

const sdk = new NodeSDK({
  serviceName: "fieldtrack-api",
  traceExporter: exporter,
  instrumentations: [
    getNodeAutoInstrumentations({
      "@opentelemetry/instrumentation-fs": { enabled: false }, // suppress noisy FS spans
    }),
  ],
});

sdk.start();

Every HTTP request, BullMQ job, and Supabase query produces a span automatically. The BullMQ worker additionally creates a manual bullmq.process_job span with job metadata attributes (job.id, session.id, job.attempts, execution_time_ms).

14.2 — Pino Log Correlation

File: src/config/logger.ts

An otelMixin function injects the active trace's trace_id, span_id, and trace_flags into every Pino log line as top-level fields:

const otelMixin = () => {
  const span = trace.getActiveSpan();
  if (!span || !span.isRecording()) return {};
  const ctx = span.spanContext();
  return {
    trace_id: ctx.traceId,
    span_id: ctx.spanId,
    trace_flags: ctx.traceFlags,
  };
};

This enables Grafana's Derived Fields in Loki to detect trace_id in log lines and render a clickable "Open in Tempo" link — navigating directly from a log entry to the corresponding trace.

When no active span exists (background workers, startup), the mixin returns {} with zero overhead.

14.3 — Prometheus Exemplars

File: src/plugins/prometheus.ts

The http_request_duration_seconds histogram is upgraded to attach trace IDs as exemplars to each observation:

httpRequestDuration.labels(labels).observeWithExemplar(
  { traceId: traceContext.traceId },
  seconds,
);

Exemplars make individual high-latency data points "clickable" in Grafana: clicking a spike in the latency graph jumps directly to the Tempo trace for that exact request.

Infrastructure requirements enabled in the standalone infra repository:

Prometheus --enable-feature=exemplar-storage flag
Backend scraped with Content-Type: application/openmetrics-text (required for exemplar ingestion)

Files Changed / Created

File	Action
`src/tracing.ts`	NEW — OpenTelemetry SDK bootstrap; OTLP exporter to Tempo
`src/server.ts`	MODIFIED — calls `initTelemetry()` at startup before app bootstrap
`src/config/logger.ts`	MODIFIED — `otelMixin` injects trace/span IDs into every log line
`src/plugins/prometheus.ts`	MODIFIED — exemplar support on duration histogram
`src/app.ts`	MODIFIED — `onRequest` hook enriches active span with route pattern and request ID

Observability Chain

HTTP Request
    │
    ├─ OpenTelemetry auto-instrumentation
    │     creates root span: http.method + http.url
    │
    ├─ onRequest hook (app.ts)
    │     sets: http.route (pattern), fastify.request_id, http.client_ip
    │
    ├─ Pino log lines
    │     include trace_id + span_id (otelMixin)
    │     → shipped to Loki via Promtail
    │
    ├─ Prometheus histogram observation
    │     exemplar: { traceId } attached
    │     → visible in Grafana latency graphs
    │
    └─ Trace exported to Tempo
          Grafana links: Loki log → Tempo trace
                         Grafana metric spike → Tempo trace

Verification Results

Check	Result
Traces appear in Tempo	Confirmed via Grafana → Explore → Tempo
`trace_id` in Pino logs	All request logs include `trace_id` field
Loki → Tempo link	Derived fields navigate from log line to trace
Prometheus exemplars	Histogram spike → Tempo trace one-click
`fs` instrumentation disabled	Noisy file-system spans suppressed

Phase 15 — API Security & Rate Limiting Overhaul

Overview

Phase 15 refactored the security layer into dedicated, isolated plugins and hardened the rate-limiting from a single in-process plugin into a Redis-backed, multi-instance-safe enforcement layer with brute-force detection and security metrics.

15.1 — Security Plugin Architecture

Security concerns were extracted from app.ts into four independent files under src/plugins/security/:

Plugin	File	Responsibility
Helmet	`helmet.plugin.ts`	Secure HTTP response headers (HSTS, X-Frame-Options, X-Content-Type-Options, etc.)
CORS	`cors.plugin.ts`	Origin allowlist from `ALLOWED_ORIGINS`; `credentials: true`
Rate Limit	`ratelimit.plugin.ts`	Redis-backed global rate limiting: 100 req/min per IP
Abuse Logging	`abuse-logging.plugin.ts`	Structured 429 logging + brute-force detection on auth routes

app.ts registers them in order: helmet → cors → rate-limit → abuse-logging.

Each plugin uses fastify-plugin (fp) to break Fastify encapsulation — they apply to the entire app, not just the scope they are registered in.

15.2 — Redis-Backed Rate Limiting

File: src/plugins/security/ratelimit.plugin.ts

await fastify.register(fastifyRateLimit, {
  global: true,
  max: 100,
  timeWindow: "1 minute",
  redis: rateLimitRedis,           // dedicated ioredis connection
  keyGenerator: (request) => request.ip,
  allowList: ["127.0.0.1", "::1"], // health checks always pass
  errorResponseBuilder: (_request, context) => ({
    success: false,
    error: "Too many requests",
    retryAfter: context.after,
  }),
});

Why Redis instead of in-memory:

	In-Memory (Phase 10)	Redis-Backed (Phase 15)
Multi-replica aware	❌ Each pod has its own counter	✅ Shared counter across all pods
Survives restart	❌ Counter resets on deploy	✅ Persists in Redis
Consistent limit	❌ N pods = N× effective limit	✅ True 100 req/min regardless of replica count

The rate-limit Redis connection is separate from the BullMQ connection to avoid contention between job queue operations and limit counters.

Route-specific limits can override the global default by setting config.rateLimit in the route options (used by location ingestion and expense creation routes).

15.3 — Brute-Force Detection & Security Metrics

File: src/plugins/security/abuse-logging.plugin.ts

An onResponse hook fires on every response. When statusCode === 429:

Logs a structured warning: { ip, route, userAgent, statusCode: 429 }
Increments security_rate_limit_hits_total{route} Prometheus counter
If the route matches an auth pattern (/auth/, /login, /sign-in, /token):
- Logs a brute-force warning: { ip, route, message: "Brute-force attempt detected" }
- Increments security_auth_bruteforce_total{ip} Prometheus counter

New Prometheus counters added to src/plugins/prometheus.ts:

Metric	Labels	Description
`security_rate_limit_hits_total`	`route`	Total 429 responses by route
`security_auth_bruteforce_total`	`ip`	Auth endpoint 429s by client IP

These feed directly into Grafana alerting rules — an ops team can receive a PagerDuty alert when security_auth_bruteforce_total exceeds a threshold.

Files Changed / Created

File	Action
`src/plugins/security/helmet.plugin.ts`	NEW — `@fastify/helmet` plugin; CSP disabled pending frontend enumeration
`src/plugins/security/cors.plugin.ts`	NEW — `@fastify/cors` from `ALLOWED_ORIGINS` with `credentials: true`
`src/plugins/security/ratelimit.plugin.ts`	NEW — Redis-backed global 100 req/min; IP allowlist; custom 429 body
`src/plugins/security/abuse-logging.plugin.ts`	NEW — 429 structured log + security Prometheus counters + brute-force detection
`src/plugins/prometheus.ts`	MODIFIED — Added `security_rate_limit_hits_total` and `security_auth_bruteforce_total` counters
`src/app.ts`	MODIFIED — Security plugins imported from `plugins/security/`; registered in order

Verification Results

Check	Result
`npx tsc --noEmit`	✅ Zero errors
Rate limit enforced globally	100 req/min per IP via Redis store
Localhost bypassed	`127.0.0.1` / `::1` exempt
429 body standardized	`{ success: false, error, retryAfter }`
Auth brute-force logged	`security_auth_bruteforce_total` incremented on auth 429s
Security metrics in Prometheus	Both counters visible at `GET /metrics`

Phase 18 — Automated Test Suite & Production Hardening

Overview

Phase 18 introduced a complete automated test suite (124 tests, 0 failures) using Vitest and Fastify's app.inject(). Alongside the tests, a set of production hardening and type-safety improvements were applied across the stack.

18.1 — Test Infrastructure

Vitest Configuration

File: vitest.config.ts

export default defineConfig({
  test: {
    globals: true,
    environment: "node",
    setupFiles: ["tests/setup/env-setup.ts"],
    clearMocks: true,
    coverage: { provider: "v8", reporter: ["text", "lcov"] },
  },
});

File: tsconfig.test.json — extends base config, adds "vitest/globals" to types, includes tests/**/*.ts.

Environment Setup

File: tests/setup/env-setup.ts

Sets all required environment variables before any module loads:

process.env["NODE_ENV"]              = "test";
process.env["SUPABASE_URL"]          = "https://placeholder.supabase.co";
process.env["SUPABASE_JWT_SECRET"]   = "test-jwt-secret-long-enough-for-hs256-32chars!!";
// ... all required env vars

Test Server Factory

File: tests/setup/test-server.ts

buildTestApp() creates a minimal Fastify instance for all integration tests:

export async function buildTestApp(): Promise<FastifyInstance> {
  const app = Fastify({ logger: false });
  await app.register(fastifyJwt, { secret: process.env["SUPABASE_JWT_SECRET"]! });
  app.setErrorHandler(/* mirrors production error handler */);
  await registerRoutes(app);
  await app.ready();
  return app;
}

Intentionally omits: security headers, rate-limit plugin, BullMQ workers, Prometheus. This keeps tests fast (< 2 s total) and externally isolated — no Redis or Supabase connections needed.

Test token helpers:

export function signEmployeeToken(app, userId?, orgId?): string
export function signAdminToken(app,   userId?, orgId?): string

UUID Test Helpers

File: tests/helpers/uuid.ts

export const TEST_UUID  = (): string => randomUUID();        // fresh v4 each call
export const TEST_UUIDS = (n: number): string[] => ...       // n unique UUIDs
export const FIXED_TEST_UUID = "00000000-0000-4000-8000-000000000000"; // deterministic

Required because Zod 4 switched to strict RFC-4122 UUID validation — hardcoded strings like "test-id" or "aaaaa..." that don't satisfy the version/variant bit pattern now fail .uuid() refinement.

18.2 — Test Coverage

Unit Tests (5 files, 67 tests)

File	What it tests
`tests/unit/utils/pagination.test.ts`	`applyPagination()` — page clamping, limit clamping, offset arithmetic, string coercion, fluent chain
`tests/unit/utils/response.test.ts`	`ok()`, `fail()`, `handleError()` — status codes, AppError dispatch, ZodError → 400, 500 fallback
`tests/unit/utils/errors.test.ts`	All custom error classes — statusCode, message, inheritance chain
`tests/unit/services/attendance.service.test.ts`	`checkIn` / `checkOut` — business rules, repository call sequence, domain errors
`tests/unit/services/expenses.service.test.ts`	`createExpense` / `updateExpenseStatus` — role enforcement, `ExpenseAlreadyReviewed` guard

Integration Tests (3 files, 57 tests)

All integration tests use app.inject() — real HTTP request/response through the full Fastify pipeline with mocked repositories:

File	Routes tested	Scenarios
`tests/integration/attendance/attendance.test.ts`	check-in, check-out, my-sessions, org-sessions	401/403/400/404/201/200, pagination, multi-tenant isolation
`tests/integration/expenses/expenses.test.ts`	POST /expenses, GET /expenses/my, GET /admin/expenses, PATCH /admin/expenses/:id	401/403/400/200/201, re-review guard, org isolation
`tests/integration/locations/locations.test.ts`	POST /locations, POST /locations/batch, GET /locations/my-route	401/403/400/201/200, batch limits, session validation, employee scoping

Mock strategy: vi.mock() is hoisted before any project imports so mocks are active when registerRoutes() triggers the import chain. Repository methods are replaced with vi.fn() and given mockResolvedValue() per-test.

18.3 — Production Hardening

`TenantContext` Abstraction

File: src/utils/tenant.ts

enforceTenant() was updated to accept a plain TenantContext object ({ organizationId: string }) in addition to a full FastifyRequest. This allows worker-path code (which has no HTTP request) to use it safely without needing to craft a fake request object or use unsafe casts.

Worker Concurrency

WORKER_CONCURRENCY env var added (default 1). Configures BullMQ worker concurrency — the default 1 ensures sequential Haversine processing (CPU-bound). Operators can increase it in staging for throughput testing.

Debug Routes Restricted to Non-Production

File: src/routes/debug.ts

if (process.env["NODE_ENV"] === "production") {
  app.log.info("Debug routes disabled in production");
  return;
}

Prevents infrastructure information disclosure (GET /debug/redis) in production.

Role Guard Idiomatic Error Throwing

File: src/middleware/role-guard.ts

requireRole() now throws ForbiddenError directly instead of manually calling reply.status(403).send(...). This routes all authorization failures through the centralized handleError pipeline, producing consistent { success: false, error, requestId } bodies.

`sequence_number` Nullable Documented

File: src/modules/locations/locations.schema.ts

Added inline documentation explaining that sequence_number is intentionally nullable during mobile app stabilization, with the planned migration SQL to make it NOT NULL once the mobile SDK is stable.

18.4 — Test Results

 Test Files  8 passed (8)
      Tests  124 passed (124)
   Duration  ~1.7s

Category	Files	Tests
Unit — utils	3	67
Unit — services	2	(included above)
Integration	3	57
Total	8	124

Files Created / Modified

File	Action
`vitest.config.ts`	NEW — Vitest config with globals, node env, setupFiles
`tsconfig.test.json`	NEW — TypeScript config for test files
`tests/setup/env-setup.ts`	NEW — Environment variable bootstrap
`tests/setup/test-server.ts`	NEW — Minimal Fastify test factory + token helpers
`tests/helpers/uuid.ts`	NEW — `TEST_UUID`, `TEST_UUIDS`, `FIXED_TEST_UUID`
`tests/unit/utils/*.test.ts`	NEW — 3 utility unit test files
`tests/unit/services/*.test.ts`	NEW — 2 service unit test files
`tests/integration/*/.test.ts`	NEW — 3 integration test files
`src/utils/tenant.ts`	MODIFIED — `TenantContext` type; `enforceTenant()` accepts both
`src/middleware/role-guard.ts`	MODIFIED — Throws `ForbiddenError`; no manual reply handling
`src/routes/debug.ts`	MODIFIED — Early return in production
`src/config/env.ts`	MODIFIED — `WORKER_CONCURRENCY` env var
`src/modules/locations/locations.schema.ts`	MODIFIED — `sequence_number` nullable documented
`package.json`	MODIFIED — `vitest`, `@vitest/coverage-v8` added; `"test"` script

Verification Results

Check	Result
`npx tsc --noEmit`	✅ Zero errors
`npm run test`	✅ 124/124 tests passing
Debug route disabled in production	`NODE_ENV=production` returns `404`
Worker concurrency configurable	`WORKER_CONCURRENCY=4` increases concurrency
Role guard errors centralized	`handleError` produces `requestId` in every 403

Post-Phase-18 — CI/CD Pipeline & Multi-Version Rollback System

Overview

Two operational hardening additions were layered on top of Phase 18:

Production-grade CI/CD pipeline — tests block deployment; Docker builds are cached
Multi-version rollback system — instant production recovery using immutable GHCR image tags

CI/CD Pipeline

File: .github/workflows/deploy.yml

The pipeline is split into two jobs:

┌─────────────────────────────────────────────────────────────┐
│  trigger: push to master OR pull_request to master           │
└─────────────────────────────────────────────────────────────┘
         │
         ▼
┌────────────────────┐         ┌─────────────────────────────┐
│  test (all events) │──pass──►│  build-and-deploy           │
│                    │         │  (push to master only)      │
│  1. npm ci         │         │                             │
│  2. tsc --noEmit   │         │  1. docker/setup-buildx     │
│  3. npm run test   │         │  2. docker/login (GHCR)     │
└────────────────────┘         │  3. docker/build-push       │
                               │     (GHA cache, 2 tags)     │
                               │  4. SSH → VPS deploy script │
                               └─────────────────────────────┘

Key improvements over the original pipeline:

Concern	Before	After
Test gate	❌ Deployed without testing	✅ `needs: test` blocks deployment on failure
Dependency install	`npm install` (non-deterministic)	`npm ci` (deterministic, lock file enforced)
TypeScript check	❌ Not run in CI	✅ `npx tsc --noEmit` before tests
Docker cache	❌ Full rebuild every push	✅ GitHub Actions cache (`type=gha`) — 80% faster
Node cache	❌ Fresh `node_modules` every run	✅ `actions/setup-node` cache on `package-lock.json`
PR validation	❌ Only runs on push	✅ `test` job runs on PRs too
Image tags	Single `latest`	`latest` + 7-char SHA tag

Multi-Version Rollback System

File: scripts/deploy.sh

Deployment History

Every successful deploy prepends the 7-char image SHA to .deploy_history (a server-side file, excluded from git):

a4f91c2   ← current (line 1)
7b3e9f1   ← previous
e2c8d34
d0a19b8
9ff3e56   ← oldest retained

The history window is capped at the last 5 deployments.

Rollback Procedure

./scripts/deploy.sh --rollback

Reads .deploy_history — requires ≥ 2 entries
Displays current and target versions with the full history
Prompts for interactive confirmation: Continue with rollback? (yes/no)
Calls deploy.sh <previous-SHA> to redeploy the previous image
The previous image is already in GHCR — no rebuild, < 10 seconds end-to-end

Deploy a Specific Historical Version

./scripts/deploy.sh 7b3e9f1

Any SHA from .deploy_history (or any valid GHCR tag) can be targeted directly.

Files Changed / Created

File	Action
`.github/workflows/deploy.yml`	MODIFIED — Split into `test` + `build-and-deploy` jobs; `npm ci`; `tsc --noEmit`; GHA cache
`scripts/deploy.sh`	MODIFIED — Unified deploy + rollback, appends SHA to `.deploy_history`; maintains 5-entry window
`.gitignore`	MODIFIED — `.deploy_history` excluded
`docs/ROLLBACK_SYSTEM.md`	NEW — Architecture, usage, troubleshooting guide
`docs/ROLLBACK_QUICKREF.md`	NEW — Fast reference card for operators

Verification Results

Check	Result
`test` job runs on PRs	Branch protection gate active
Deployment blocked on test failure	`needs: test` enforced
`npm ci` used	Deterministic dependency install
Docker layer cache	`cache-from/to: type=gha` in `docker/build-push-action`
Rollback requires 2+ deployments	Script exits with error if history is insufficient
Rollback time	< 10 s (image already in GHCR)
SHA tag on each image	`ghcr.io/.../fieldtrack-api:<sha>` retained permanently

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FieldTrack 2.0 Backend — Walkthrough

Phase 0 — Project Scaffolding

Phase 1 — Secure Tenant Isolation Layer

Files Changed / Created

How Tenant Enforcement Works

Phase 2 — Attendance Module (Check-in / Check-out)

Architecture: Route → Controller → Service → Repository

Files Created

Endpoints

Business Rules

Example curl Requests

Verification Results

Phase 3 — Location Ingestion System

Files Created

Endpoints

Business Rules

Suggested Database Indexes (Phase 3 Prep)

Example curl Requests

Phase 4 — Location Bulk Ingestion (Production-Optimized)

Architecture Upgrade

Additional Endpoint

Batch Payload Schema

Enterprise Optimizations & Business Rules

Example Batch curl Request

Suggested Database Schema & Partitioning Strategy

Phase 5 — Per-User Rate Limiting & Ingestion Telemetry

Overview

5.1 — Per-User Rate Limiting

5.2 — Ingestion Telemetry

Files Changed

Verification Results

Phase 6 — Distance Engine & Session Summary

Architecture Overview

Schema: session_summaries

Endpoints

Performance Considerations & Idempotency

Phase 7 — Asynchronous Background Workers (Decoupled Compute)

Architecture Overview

How it Works

Architectural Risks & Limitations (MVP Scope)

Phase 7.5 — Crash Recovery & Self-Healing

Architecture Overview

Phase 8 — Expense Module & Architecture Cleanup

Part 1 — Domain Layer Removal

Part 2 — Secured /internal/metrics

Part 3 — Expense Module

Architecture: Route → Controller → Service → Repository

Files Created

Database Schema

Endpoints

Business Rules

Zod Validation Rules

Tenant Isolation

Structured Log Events

Rate Limiting

Index Strategy

Example curl Requests

Verification Results

Phase 9 — Admin Analytics Layer

Architecture: Route → Controller → Service → Repository

Files Created

Endpoints

Endpoint 1 — GET /admin/org-summary

Endpoint 2 — GET /admin/user-summary

Endpoint 3 — GET /admin/top-performers

Aggregation Strategy and Performance

Two-Query Pattern

Why Not Direct session_summaries Scan

Tenant Isolation

Zod Validation Summary

Index Dependencies

Example curl Requests

Verification Results

Phase 10 — Production Hardening & Enterprise Correctness

Schema: `session_summaries`

Part 2 — Secured `/internal/metrics`

Registration in `src/app.ts`

`src/utils/response.ts`

`src/utils/pagination.ts`

`src/utils/errors.ts` — Domain Error Classes

`src/modules/attendance/attendance.repository.ts`

`src/modules/attendance/attendance.service.ts`

`src/modules/expenses/expenses.repository.ts`

`src/modules/expenses/expenses.service.ts`

`src/modules/locations/locations.repository.ts`