# TrustOS Architecture Documentation

This document provides a detailed overview of the TrustOS system architecture, design decisions, data flow, and technical implementation details.

---

## Table of Contents

- [System Overview](#system-overview)
- [Architecture Principles](#architecture-principles)
- [Component Architecture](#component-architecture)
- [Data Model](#data-model)
- [Authentication & Authorization](#authentication--authorization)
- [API Design](#api-design)
- [Frontend Architecture](#frontend-architecture)
- [Backend Architecture](#backend-architecture)
- [Database Design](#database-design)
- [AI Integration](#ai-integration)
- [Security Architecture](#security-architecture)
- [Scalability Considerations](#scalability-considerations)
- [Performance Optimization](#performance-optimization)

---

## System Overview

TrustOS is a multi-tenant, AI-powered cyber resilience platform built on a modern microservices-inspired architecture. The system is designed to be:

- **Secure**: Multi-tenant isolation with defense-in-depth security
- **Scalable**: Async I/O throughout for high concurrency
- **Maintainable**: Clean separation of concerns and modular design
- **Resilient**: Graceful degradation when external services are unavailable

### High-Level Architecture

```
┌─────────────────────────────────────────────────────────────────┐
│                        Client Layer                             │
│  Web Browser (Executive, IT Admin, TrustOS Admin)              │
└────────────────────┬────────────────────────────────────────────┘
                     │ HTTPS
┌────────────────────▼────────────────────────────────────────────┐
│                      Frontend Layer                             │
│  Next.js 16 + TypeScript + Tailwind CSS + shadcn/ui             │
│  - Server-Side Rendering (SSR)                                  │
│  - Client-Side Hydration                                         │
│  - Static Site Generation (SSG) where applicable                 │
└────────────────────┬────────────────────────────────────────────┘
                     │ REST API (JSON)
┌────────────────────▼────────────────────────────────────────────┐
│                       API Gateway                               │
│  FastAPI Application                                            │
│  - Request Validation (Pydantic)                                 │
│  - Authentication (JWT)                                          │
│  - Authorization (RBAC)                                          │
│  - Rate Limiting (future)                                       │
│  - Request Logging                                              │
└────────────────────┬────────────────────────────────────────────┘
                     │
        ┌────────────┴────────────┐
        │                         │
┌───────▼────────┐       ┌────────▼─────────┐
│  Service Layer │       │  Background      │
│                │       │  Workers         │
│ - Dashboard    │       │ - AI Translation│
│ - Findings     │       │ - Risk Calc     │
│ - Reports      │       │ - PDF Gen       │
│ - Footprint    │       │ - Monitoring    │
└───────┬────────┘       └────────┬─────────┘
        │                         │
┌───────▼─────────────────────────▼──────────┐
│              Data Access Layer                │
│  SQLAlchemy 2.0 (Async ORM)                   │
│  - Query Building                            │
│  - Connection Pooling                        │
│  - Transaction Management                   │
└────────────────────┬─────────────────────────┘
                     │
┌────────────────────▼─────────────────────────┐
│              Database Layer                   │
│  PostgreSQL 16                                │
│  - Multi-Tenant Data Isolation               │
│  - Indexing Strategy                         │
│  - Foreign Key Constraints                   │
│  - JSONB for Flexible Data                   │
└──────────────────────────────────────────────┘

External Services:
┌──────────────┐  ┌──────────────┐  ┌──────────────┐
│ OpenAI API   │  │ Anthropic API│  │ HIBP API     │
└──────────────┘  └──────────────┘  └──────────────┘
```

---

## Architecture Principles

### 1. Authorization First

TrustOS only scans and monitors assets that have been explicitly authorized by the tenant organization. This is a core security and privacy principle:

- **Authorized Assets Table**: All monitored assets must be pre-registered
- **Scope Enforcement**: All automated checks respect the authorized asset list
- **Executive Enrollment**: Executive monitoring requires explicit organizational consent
- **Audit Trail**: All authorization decisions are logged

### 2. Multi-Tenant Isolation

Every data access path enforces tenant isolation at multiple layers:

- **Database Level**: All tables include `tenant_id` with foreign key constraints
- **ORM Level**: Queries automatically filter by tenant_id
- **API Level**: Middleware validates tenant access before processing requests
- **Application Level**: UI components only display tenant-specific data

### 3. Privacy by Design

Executive and organizational data is handled with privacy as a foundational requirement:

- **Minimal Data Collection**: Only collect data necessary for security assessments
- **Explicit Consent**: Executive enrollment requires organizational authorization
- **Data Minimization**: Store only what, not who, where possible
- **Audit Logging**: All data access is logged for accountability

### 4. AI-Augmented, Not AI-Dependent

AI features enhance the product but are not required for core functionality:

- **Graceful Degradation**: Features work with raw technical data if AI is unavailable
- **Caching**: AI responses are cached to avoid redundant API calls
- **Fallback Mechanisms**: System continues operating if AI services are down
- **Cost Control**: Rate limiting and caching to manage AI API costs

### 5. Audit Trail

All state changes are tracked with full provenance:

- **Timestamps**: `created_at` and `updated_at` on all records
- **User Attribution**: `created_by` and `updated_by` where applicable
- **Status Changes**: Finding status transitions are logged with notes
- **Access Logs**: API requests are logged with user and tenant context

---

## Component Architecture

### Frontend Components

#### Page Components
- **Dashboard Page** (`/dashboard`): Executive view with risk score, top risks, trends
- **Findings Page** (`/findings`): IT admin view with sortable/filterable table
- **Finding Detail Page** (`/findings/[id]`): Detailed view with technical and business impact
- **Login Page** (`/login`): Authentication interface
- **Footprint Page** (`/footprint`): Digital footprint center

#### Reusable Components)
- **RiskDial**: Circular gauge for cyber health score (0-100)
- **RiskCard**: Card displaying finding with AI summary and impact
- **TrendChart**: Line chart for 90-day risk history
- **RemediationBoard**: Kanban board for finding status tracking
- **Badge**: Severity and status badges with color coding

#### Hooks
- **useAuth**: Authentication state management (token, role, tenant_id)
- **useDashboard**: Dashboard data fetching and caching
- **useFindings**: Findings list and detail fetching

### Backend Components

#### API Routes
- **auth.py**: Login, token refresh, user info
- **dashboard.py**: Dashboard data aggregation
- **findings.py**: Findings CRUD operations
- **reports.py**: Audit report generation
- **attack_paths.py**: Attack path visualization
- **footprint.py**: Digital footprint data
- **ai.py**: AI translation and coaching

#### Services
- **ai_translator.py**: OpenAI/Anthropic integration for risk translation
- **risk_calculator.py**: Risk score calculation algorithm
- **report_generator.py**: PDF report generation with Jinja2/WeasyPrint

#### Core
- **config.py**: Configuration management with Pydantic Settings
- **security.py**: JWT token management, password hashing, RBAC decorators

---

## Data Model

### Entity Relationship Diagram

```
┌─────────────┐       ┌─────────────┐       ┌─────────────┐
│   tenants   │───────│    users    │───────│  findings   │
│─────────────│ 1:N   │─────────────│ 1:N   │─────────────│
│ id (PK)     │       │ id (PK)     │       │ id (PK)     │
│ name        │       │ tenant_id   │       │ tenant_id   │
│ slug        │       │ email       │       │ asset_id    │
│ industry    │       │ role        │       │ executive_id│
│ size_range  │       │ ...         │       │ severity    │
│ ...         │       └─────────────┘       │ status      │
└─────────────┘                            │ category    │
         │                                  │ ai_summary  │
         │                                  │ ...         │
         │                                  └─────────────┘
         │                                           │
         │                                           │
┌─────────────┐                            ┌───────────▼──────────┐
│   assets    │                            │    risk_scores       │
│─────────────│                            │──────────────────────│
│ id (PK)     │                            │ id (PK)             │
│ tenant_id   │                            │ tenant_id           │
│ name        │                            │ score_date          │
│ asset_type  │                            │ overall_score       │
│ value       │                            │ score_identity      │
│ ...         │                            │ score_cloud         │
└─────────────┘                            │ ...                 │
                                           └──────────────────────┘

┌─────────────┐       ┌─────────────┐       ┌─────────────┐
│ executives  │       │authorized   │       │attack_paths │
│─────────────│       │  assets    │       │─────────────│
│ id (PK)     │       │─────────────│       │ id (PK)     │
│ tenant_id   │       │ id (PK)     │       │ finding_id  │
│ full_name   │       │ tenant_id   │       │ title       │
│ title       │       │ value       │       │ ai_narrative│
│ email       │       │ asset_type  │       │ nodes_json  │
│ ...         │       │ ...         │       │ edges_json  │
└─────────────┘       └─────────────┘       └─────────────┘

┌─────────────┐
│audit_reports│
│─────────────│
│ id (PK)     │
│ tenant_id   │
│ title       │
│ report_date │
│ baseline_   │
│   score     │
│ pdf_path    │
│ ...         │
└─────────────┘
```

### Key Tables

#### tenants
Organizational units with complete data isolation.

- `id`: UUID primary key
- `name`: Organization display name
- `slug`: URL-friendly identifier (unique)
- `industry`: Industry classification
- `size_range`: Company size (SMB, mid-market, enterprise)
- `contact_email`: Primary contact
- `is_active`: Active status for soft deletes

#### users
User accounts with role-based access control.

- `id`: UUID primary key
- `tenant_id`: Foreign key to tenants
- `email`: Unique email address
- `hashed_password`: Bcrypt hash
- `role`: enum (executive, it_admin, trustos_admin)
- `is_active`: Account status

#### findings
Security vulnerabilities and exposures.

- `id`: UUID primary key
- `tenant_id`: Foreign key to tenants
- `asset_id`: Foreign key to assets (nullable)
- `executive_id`: Foreign key to executives (nullable)
- `title`: Human-readable title
- `severity`: enum (critical, high, medium, low, info)
- `status`: enum (open, in_progress, resolved, verified)
- `category`: enum (external_exposure, cloud_posture, credential_exposure, etc.)
- `technical_description`: Raw technical details
- `cve_id`: CVE identifier (if applicable)
- `cvss_score`: CVSS score (if applicable)
- `ai_summary`: AI-generated plain-English summary
- `ai_business_impact`: AI-generated business impact
- `ai_remediation_steps`: AI-generated fix steps
- `assignee_email`: Assigned team member
- `due_date`: Remediation deadline
- `is_top_risk`: Flag for top 3 risks

#### risk_scores
Daily snapshots of risk metrics.

- `id`: UUID primary key
- `tenant_id`: Foreign key to tenants
- `score_date`: Timestamp of snapshot
- `overall_score`: 0-100 overall score
- `score_identity`: Identity security score
- `score_cloud`: Cloud posture score
- `score_network`: Network security score
- `score_web`: Web application score
- `score_credential`: Credential security score
- `score_digital_footprint`: Digital footprint score
- `score_third_party`: Third-party risk score
- `critical_count`: Count of critical findings
- `high_count`: Count of high findings
- `medium_count`: Count of medium findings
- `low_count`: Count of low findings

---

## Authentication & Authorization

### Authentication Flow

```
1. User submits credentials to POST /api/v1/auth/login
   ↓
2. Backend validates credentials against database
   ↓
3. Backend generates JWT token with:
   - sub: user_id
   - role: user_role
   - tenant_id: tenant_id
   - exp: expiration timestamp
   ↓
4. Frontend stores token in localStorage
   ↓
5. Frontend includes token in Authorization header: Bearer <token>
   ↓
6. Backend validates token on each protected request
   ↓
7. Backend extracts user context from token
   ↓
8. Request proceeds with user context
```

### JWT Token Structure

```json
{
  "sub": "user-uuid",
  "role": "executive",
  "tenant_id": "tenant-uuid",
  "exp": 1234567890,
  "iat": 1234567890
}
```

### Role-Based Access Control (RBAC)

Three roles with distinct permissions:

#### Executive
- **Can View**: Dashboard, risk scores, AI summaries, trends
- **Cannot View**: Raw CVE data, technical details, other tenants
- **Can Modify**: None (read-only)

#### IT Admin
- **Can View**: All findings, technical details, CVEs, remediation steps
- **Can Modify**: Finding status, assignees, due dates, resolution notes
- **Cannot View**: Other tenants' data

#### TrustOS Admin
- **Can View**: All tenants, all data, system metrics
- **Can Modify**: Tenant settings, authorized assets, audit reports
- **Can Manage**: Users, roles, system configuration

### Authorization Middleware

```python
# Example from app/core/security.py
def require_executive_or_above(payload: dict = Depends(verify_token)):
    if payload.get("role") not in ["executive", "it_admin", "trustos_admin"]:
        raise HTTPException(status_code=403, detail="Insufficient permissions")
    return payload

def require_it_or_above(payload: dict = Depends(verify_token)):
    if payload.get("role") not in ["it_admin", "trustos_admin"]:
        raise HTTPException(status_code=403, detail="Insufficient permissions")
    return payload

def require_admin(payload: dict = Depends(verify_token)):
    if payload.get("role") != "trustos_admin":
        raise HTTPException(status_code=403, detail="Admin access required")
    return payload
```

---

## API Design

### RESTful Conventions

TrustOS follows RESTful API design principles:

- **Resource-Based URLs**: `/api/v1/findings`, `/api/v1/tenants`
- **HTTP Methods**: GET (read), POST (create), PATCH (update), DELETE (delete)
- **Status Codes**: 200 (success), 201 (created), 400 (bad request), 401 (unauthorized), 403 (forbidden), 404 (not found), 500 (server error)
- **JSON Request/Response**: All data is JSON-encoded
- **Versioning**: `/api/v1/` prefix for future compatibility

### API Response Format

#### Success Response
```json
{
  "data": { ... },
  "meta": {
    "timestamp": "2024-01-01T00:00:00Z",
    "request_id": "uuid"
  }
}
```

#### Error Response
```json
{
  "error": {
    "code": "VALIDATION_ERROR",
    "message": "Invalid input data",
    "details": { ... }
  },
  "meta": {
    "timestamp": "2024-01-01T00:00:00Z",
    "request_id": "uuid"
  }
}
```

### Key API Endpoints

#### Authentication
- `POST /api/v1/auth/login` - Authenticate and receive token
- `GET /api/v1/auth/me` - Get current user info

#### Dashboard
- `GET /api/v1/dashboard?tenant_id={id}` - Get dashboard data

#### Findings
- `GET /api/v1/findings?tenant_id={id}` - List findings
- `GET /api/v1/findings/{id}` - Get finding detail
- `POST /api/v1/findings` - Create finding (IT Admin+)
- `PATCH /api/v1/findings/{id}/status` - Update finding status (IT Admin+)

#### Reports
- `GET /api/v1/audit-reports?tenant_id={id}` - List audit reports
- `POST /api/v1/audit-reports/generate` - Generate audit report (Admin)

#### AI
- `POST /api/v1/ai/translate/{finding_id}` - Trigger AI translation (IT Admin+)
- `GET /api/v1/ai/explain/{finding_id}?question=...` - AI Security Coach (IT Admin+)

---

## Frontend Architecture

### Next.js App Router Structure

```
src/app/
├── layout.tsx          # Root layout with providers
├── page.tsx            # Root redirect to /login
├── login/
│   └── page.tsx        # Login page
├── dashboard/
│   └── page.tsx        # Executive dashboard
├── findings/
│   ├── page.tsx        # Findings list
│   └── [id]/
│       └── page.tsx    # Finding detail
└── footprint/
    └── page.tsx        # Digital footprint center
```

### State Management

TrustOS uses React Context for global state:

```typescript
// Auth Context
interface AuthContext {
  token: string | null;
  role: UserRole | null;
  tenantId: string | null;
  name: string | null;
  login: (email: string, password: string) => Promise<void>;
  logout: () => void;
}
```

### API Client

Custom API client with token management:

```typescript
const api = {
  login: (email: string, password: string) => 
    fetch('/api/v1/auth/login', { method: 'POST', body: ... }),
  
  dashboard: (tenantId: string) => 
    fetch(`/api/v1/dashboard?tenant_id=${tenantId}`, {
      headers: { Authorization: `Bearer ${token}` }
    }),
  
  // ... other methods
};
```

### Component Design Patterns

#### Presentational Components
- Receive data via props
- No side effects
- Reusable across contexts

#### Container Components
- Fetch data from API
- Manage state
- Pass data to presentational components

#### Higher-Order Components
- `withAuth`: Wraps components requiring authentication
- `withRole`: Wraps components requiring specific roles

---

## Backend Architecture

### FastAPI Application Structure

```python
# app/main.py
from fastapi import FastAPI
from fastapi.middleware.cors import CORSMiddleware

app = FastAPI(
    title="TrustOS API",
    version="1.0.0",
    description="AI-powered cyber resilience platform"
)

# CORS middleware
app.add_middleware(
    CORSMiddleware,
    allow_origins=["http://localhost:3000"],
    allow_credentials=True,
    allow_methods=["*"],
    allow_headers=["*"],
)

# Include routers
app.include_router(auth.router, prefix="/api/v1/auth", tags=["auth"])
app.include_router(dashboard.router, prefix="/api/v1/dashboard", tags=["dashboard"])
# ... other routers

@app.on_event("startup")
async def startup_event():
    # Create tables in development
    if settings.DEBUG:
        async with engine.begin() as conn:
            await conn.run_sync(Base.metadata.create_all)

@app.get("/health")
async def health_check():
    return {"status": "healthy"}
```

### Dependency Injection

FastAPI's dependency system for authentication and database:

```python
# Database session
async def get_db() -> AsyncSession:
    async with AsyncSessionLocal() as session:
        try:
            yield session
        finally:
            await session.close()

# Authentication
async def verify_token(authorization: str = Header(...)) -> dict:
    token = authorization.replace("Bearer ", "")
    payload = decode_jwt(token)
    return payload

# Protected route
@router.get("/dashboard")
async def get_dashboard(
    tenant_id: str,
    payload: dict = Depends(verify_token),
    db: AsyncSession = Depends(get_db)
):
    # Access payload['role'], payload['tenant_id']
    # Use db for database operations
    ...
```

### Service Layer Pattern

Business logic separated from API routes:

```python
# app/services/risk_calculator.py
async def recalculate_risk_score(tenant_id: str, db: AsyncSession) -> float:
    # Business logic for risk calculation
    findings = await get_open_findings(tenant_id, db)
    score = calculate_score(findings)
    await save_risk_snapshot(tenant_id, score, db)
    return score

# API route uses service
@router.patch("/findings/{id}/status")
async def update_status(finding_id: str, body: StatusUpdate, db: AsyncSession = Depends(get_db)):
    finding = await get_finding(finding_id, db)
    finding.status = body.status
    await db.commit()
    
    # Trigger background risk recalculation
    asyncio.create_task(recalculate_risk_score(finding.tenant_id))
    
    return finding
```

---

## Database Design

### Schema Design Principles

1. **Multi-Tenant by Default**: All tables include `tenant_id`
2. **UUID Primary Keys**: Distributed-friendly, no sequence contention
3. **Soft Deletes**: `is_active` flags instead of hard deletes
4. **Audit Fields**: `created_at`, `updated_at` on all tables
5. **JSONB for Flexibility**: Store semi-structured data in JSONB columns

### Indexing Strategy

```sql
-- Tenant isolation (every query)
CREATE INDEX idx_findings_tenant_id ON findings(tenant_id);

-- Common query patterns
CREATE INDEX idx_findings_status ON findings(status);
CREATE INDEX idx_findings_severity ON findings(severity);
CREATE INDEX idx_findings_category ON findings(category);
CREATE INDEX idx_findings_tenant_status ON findings(tenant_id, status);

-- Time-series queries
CREATE INDEX idx_risk_scores_tenant_date ON risk_scores(tenant_id, score_date DESC);

-- Unique constraints
CREATE UNIQUE INDEX idx_users_email ON users(email);
CREATE UNIQUE INDEX idx_tenants_slug ON tenants(slug);
```

### Connection Pooling

```python
# SQLAlchemy async engine with connection pooling
engine = create_async_engine(
    settings.DATABASE_URL,
    echo=False,
    pool_pre_ping=True,  # Verify connections before use
    pool_size=10,       # Base pool size
    max_overflow=20,     # Additional connections under load
)
```

---

## AI Integration

### AI Service Architecture

```
┌─────────────┐
│  API Route  │
└──────┬──────┘
       │
┌──────▼──────────┐
│ AI Translator   │
│ Service         │
└──────┬──────────┘
       │
┌──────▼──────────┐
│ LLM Provider    │
│ (OpenAI/Anthropic)│
└─────────────────┘
```

### AI Translation Flow

```python
# 1. Finding created or updated
finding = Finding(...)

# 2. Trigger AI translation (background task)
asyncio.create_task(translate_finding_async(finding.id))

# 3. AI service constructs prompt
prompt = f"""
Translate this cybersecurity finding:
Title: {finding.title}
Severity: {finding.severity}
CVE ID: {finding.cve_id}
Technical Description: {finding.technical_description}
"""

# 4. Call LLM with system prompt
system_prompt = """
You are TrustOS, an AI cyber resilience advisor.
Translate technical findings into plain-English business impact.
Output JSON with: summary, business_impact, impact_level, remediation_steps.
"""

# 5. Parse and store AI response
data = json.loads(llm_response)
finding.ai_summary = data["summary"]
finding.ai_business_impact = data["business_impact"]
finding.ai_remediation_steps = data["remediation_steps"]
await db.commit()
```

### AI Provider Selection

```python
# app/core/config.py
AI_PROVIDER = os.getenv("AI_PROVIDER", "openai")  # or "anthropic"

# app/services/ai_translator.py
if settings.AI_PROVIDER == "openai":
    client = AsyncOpenAI(api_key=settings.OPENAI_API_KEY)
    response = await client.chat.completions.create(
        model="gpt-4o-mini",
        messages=[...],
        response_format={"type": "json_object"}
    )
elif settings.AI_PROVIDER == "anthropic":
    client = AsyncAnthropic(api_key=settings.ANTHROPIC_API_KEY)
    response = await client.messages.create(
        model="claude-3-haiku-20240307",
        messages=[...]
    )
```

### AI Caching Strategy

- **Store AI Responses**: AI translations are stored in the database
- **Avoid Redundant Calls**: Check if `ai_summary` exists before re-translating
- **Background Processing**: AI calls are async and non-blocking
- **Graceful Degradation**: If AI fails, use raw technical description

---

## Security Architecture

### Defense in Depth

```
┌─────────────────────────────────────────────────────────┐
│ 1. Network Security                                      │
│    - HTTPS/TLS encryption                                │
│    - CORS restrictions                                   │
│    - Rate limiting (planned)                             │
└─────────────────────────────────────────────────────────┘
┌─────────────────────────────────────────────────────────┐
│ 2. Authentication                                         │
│    - JWT token validation                                 │
│    - Token expiration (8 hours)                          │
│    - Secure password hashing (bcrypt)                     │
└─────────────────────────────────────────────────────────┘
┌─────────────────────────────────────────────────────────┐
│ 3. Authorization                                          │
│    - Role-based access control                           │
│    - Tenant isolation enforcement                        │
│    - Route-level permission checks                       │
└─────────────────────────────────────────────────────────┘
┌─────────────────────────────────────────────────────────┐
│ 4. Input Validation                                       │
│    - Pydantic schema validation                          │
│    - SQL injection prevention (ORM)                      │
│    - XSS prevention (React escaping)                     │
└─────────────────────────────────────────────────────────┘
┌─────────────────────────────────────────────────────────┐
│ 5. Data Security                                         │
│    - Multi-tenant database isolation                     │
│    - Encrypted secrets management                        │
│    - Audit logging                                       │
└─────────────────────────────────────────────────────────┘
```

### Security Headers

```python
# app/main.py
from fastapi.middleware.trustedhost import TrustedHostMiddleware

app.add_middleware(
    TrustedHostMiddleware,
    allowed_hosts=["trustos.com", "*.trustos.com"]
)

# Additional headers via middleware
@app.middleware("http")
async def add_security_headers(request: Request, call_next):
    response = await call_next(request)
    response.headers["X-Content-Type-Options"] = "nosniff"
    response.headers["X-Frame-Options"] = "DENY"
    response.headers["X-XSS-Protection"] = "1; mode=block"
    response.headers["Strict-Transport-Security"] = "max-age=31536000; includeSubDomains"
    return response
```

### Secrets Management

- **Environment Variables**: All secrets in `.env` files (git-ignored)
- **Production**: Use secret management services (AWS Secrets Manager, HashiCorp Vault)
- **Rotation**: Regular API key rotation policy
- **Least Privilege**: Database users have minimal required permissions

---

## Scalability Considerations

### Horizontal Scaling

The architecture supports horizontal scaling:

- **Stateless API**: FastAPI instances can be scaled horizontally
- **Database Connection Pooling**: Efficient connection reuse
- **Async I/O**: High concurrency with minimal threads
- **Load Balancer**: Nginx or cloud load balancer in front of API

### Vertical Scaling

- **Database**: PostgreSQL can scale vertically (more CPU/RAM)
- **Caching**: Redis planned for session and query caching
- **CDN**: Frontend static assets served via CDN

### Performance Optimization Strategies

1. **Database Optimization**
   - Proper indexing on frequently queried columns
   - Query optimization with EXPLAIN ANALYZE
   - Connection pooling to reduce overhead
   - Read replicas for read-heavy workloads (future)

2. **API Optimization**
   - Response compression (gzip)
   - Pagination for large result sets
   - Selective field loading (avoid SELECT *)
   - Async operations throughout

3. **Frontend Optimization**
   - Code splitting with Next.js
   - Image optimization
   - Static generation where possible
   - Client-side caching

4. **Caching Strategy**
   - API response caching (Redis)
   - Static asset caching (CDN)
   - AI response caching (database)
   - Browser caching headers

---

## Performance Optimization

### Database Query Optimization

```python
# Bad: N+1 query problem
for finding in findings:
    asset = await get_asset(finding.asset_id)  # N queries

# Good: Eager loading
findings = await db.execute(
    select(Finding).options(selectinload(Finding.asset))
)
```

### API Response Optimization

```python
# Bad: Return all fields
@router.get("/findings")
async def list_findings():
    return await db.execute(select(Finding))

# Good: Select only needed fields
@router.get("/findings")
async def list_findings():
    return await db.execute(
        select(Finding.id, Finding.title, Finding.severity)
    )
```

### Frontend Performance

```typescript
// Bad: Re-render on every state change
useEffect(() => {
  fetchData();
}, [state]); // Runs on every state change

// Good: Only re-fetch when dependencies change
useEffect(() => {
  fetchData();
}, [tenantId, filter]); // Only runs when tenant or filter changes
```

---

## Monitoring & Observability

### Logging Strategy

```python
# Structured logging
import logging
logger = logging.getLogger(__name__)

logger.info(
    "Finding status updated",
    extra={
        "finding_id": finding.id,
        "old_status": old_status,
        "new_status": new_status,
        "user_id": user_id,
        "tenant_id": tenant_id
    }
)
```

### Metrics to Track

- **API Metrics**: Request rate, error rate, response time
- **Database Metrics**: Query time, connection pool usage
- **Business Metrics**: Active tenants, findings created, risk score trends
- **AI Metrics**: API calls, token usage, cost tracking

### Health Checks

```python
@app.get("/health")
async def health_check():
    checks = {
        "database": await check_database(),
        "ai_service": await check_ai_service(),
        "storage": await check_storage()
    }
    status = "healthy" if all(checks.values()) else "degraded"
    return {"status": status, "checks": checks}
```

---

## Future Architecture Enhancements

### Planned Improvements

1. **Message Queue**: Celery + Redis for background job processing
2. **Caching Layer**: Redis for session and query caching
3. **Read Replicas**: PostgreSQL read replicas for scaling reads
4. **Microservices**: Split into separate services (auth, findings, monitoring)
5. **Event Sourcing**: Event-driven architecture for audit trail
6. **GraphQL**: Alternative to REST for complex queries
7. **Real-time Updates**: WebSocket for live dashboard updates
8. **Edge Computing**: Cloudflare Workers for global distribution

---

## Conclusion

The TrustOS architecture is designed to be secure, scalable, and maintainable while following modern best practices. The multi-tenant isolation, AI augmentation, and authorization-first principles ensure the platform can grow with customer needs while maintaining security and privacy.

For questions or contributions to the architecture, please refer to the [CONTRIBUTING.md](CONTRIBUTING.md) guide.