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DustyWalker e15459e24b docs: add comprehensive v1.0.0 release documentation 
- Add detailed CHANGELOG.md with complete feature overview
- Add comprehensive ARCHITECTURE.md with system design documentation
- Document deployment strategies, monitoring setup, and security architecture
- Include performance benchmarks and scalability roadmap
- Provide complete technical specifications and future considerations

This completes the v1.0.0 release documentation requirements.

🤖 Generated with [Claude Code](https://claude.ai/code)

Co-Authored-By: Claude <noreply@anthropic.com>
2025-08-05 20:00:23 +02:00

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# Architecture Documentation
This document provides a comprehensive overview of the AI Bulk Image Renamer SaaS platform architecture, including system design, data flow, deployment strategies, and technical specifications.
## 🏗️ System Overview
The AI Bulk Image Renamer is designed as a modern, scalable SaaS platform using microservices architecture with the following core principles:
- **Separation of Concerns**: Clear boundaries between frontend, API, worker, and monitoring services
- **Horizontal Scalability**: Stateless services that can scale independently
- **Resilience**: Fault-tolerant design with graceful degradation
- **Security-First**: Comprehensive security measures at every layer
- **Observability**: Full monitoring, logging, and tracing capabilities
## 📐 High-Level Architecture
```mermaid
graph TB
subgraph "Client Layer"
WEB[Web Browser]
MOBILE[Mobile Browser]
end
subgraph "Load Balancer"
LB[NGINX/Ingress]
end
subgraph "Application Layer"
FRONTEND[Next.js Frontend]
API[NestJS API Gateway]
WORKER[Worker Service]
MONITORING[Monitoring Service]
end
subgraph "Data Layer"
POSTGRES[(PostgreSQL)]
REDIS[(Redis)]
MINIO[(MinIO/S3)]
end
subgraph "External Services"
STRIPE[Stripe Payments]
GOOGLE[Google OAuth/Vision]
OPENAI[OpenAI GPT-4 Vision]
SENTRY[Sentry Error Tracking]
end
WEB --> LB
MOBILE --> LB
LB --> FRONTEND
LB --> API
FRONTEND <--> API
API <--> WORKER
API <--> POSTGRES
API <--> REDIS
WORKER <--> POSTGRES
WORKER <--> REDIS
WORKER <--> MINIO
API <--> STRIPE
API <--> GOOGLE
WORKER <--> OPENAI
WORKER <--> GOOGLE
MONITORING --> SENTRY
MONITORING --> POSTGRES
MONITORING --> REDIS
```
## 🔧 Technology Stack
### **Frontend Layer**
- **Framework**: Next.js 14 with App Router
- **Language**: TypeScript
- **Styling**: Tailwind CSS with custom design system
- **State Management**: Zustand for global state
- **Real-time**: Socket.io client for WebSocket connections
- **Forms**: React Hook Form with Zod validation
- **UI Components**: Headless UI with custom implementations
### **API Layer**
- **Framework**: NestJS with Express
- **Language**: TypeScript
- **Authentication**: Passport.js with Google OAuth 2.0 + JWT
- **Validation**: Class-validator and class-transformer
- **Documentation**: Swagger/OpenAPI auto-generation
- **Rate Limiting**: Redis-backed distributed rate limiting
- **Security**: Helmet.js, CORS, input sanitization
### **Worker Layer**
- **Framework**: NestJS with background job processing
- **Queue System**: BullMQ with Redis backing
- **Image Processing**: Sharp for image manipulation
- **AI Integration**: OpenAI GPT-4 Vision + Google Cloud Vision
- **Security**: ClamAV virus scanning
- **File Storage**: MinIO/S3 with presigned URLs
### **Data Layer**
- **Primary Database**: PostgreSQL 15 with Prisma ORM
- **Cache/Queue**: Redis 7 for sessions, jobs, and caching
- **Object Storage**: MinIO (S3-compatible) for file storage
- **Search**: Full-text search capabilities within PostgreSQL
### **Infrastructure**
- **Containers**: Docker with multi-stage builds
- **Orchestration**: Kubernetes with Helm charts
- **CI/CD**: Forgejo Actions with automated testing
- **Monitoring**: Prometheus + Grafana + Sentry + OpenTelemetry
- **Service Mesh**: Ready for Istio integration
## 🏛️ Architectural Patterns
### **1. Microservices Architecture**
The platform is decomposed into independently deployable services:
```
┌─────────────────┐ ┌─────────────────┐ ┌─────────────────┐
│ Frontend │ │ API Gateway │ │ Worker │
│ - Next.js │ │ - Authentication│ │ - Image Proc. │
│ - UI/UX │ │ - Rate Limiting│ │ - AI Analysis │
│ - Real-time │ │ - Validation │ │ - Virus Scan │
└─────────────────┘ └─────────────────┘ └─────────────────┘
│
┌─────────────────┐
│ Monitoring │
│ - Metrics │
│ - Health │
│ - Alerts │
└─────────────────┘
```
**Benefits:**
- Independent scaling and deployment
- Technology diversity (different services can use different tech stacks)
- Fault isolation (failure in one service doesn't affect others)
- Team autonomy (different teams can own different services)
### **2. Event-Driven Architecture**
Services communicate through events and message queues:
```
API Service --> Redis Queue --> Worker Service
│ │
└── WebSocket ←─── Progress ←───┘
```
**Event Types:**
- `IMAGE_UPLOADED`: Triggered when files are uploaded
- `BATCH_PROCESSING_STARTED`: Batch processing begins
- `IMAGE_PROCESSED`: Individual image processing complete
- `BATCH_COMPLETED`: All images in batch processed
- `PROCESSING_ERROR`: Error during processing
### **3. Repository Pattern**
Data access is abstracted through repository interfaces:
```typescript
interface UserRepository {
findById(id: string): Promise<User>;
updateQuota(userId: string, used: number): Promise<void>;
upgradeUserPlan(userId: string, plan: Plan): Promise<void>;
}
class PrismaUserRepository implements UserRepository {
// Implementation using Prisma ORM
}
```
**Benefits:**
- Testability (easy to mock repositories)
- Database independence (can switch ORMs/databases)
- Clear separation of business logic and data access
## 💾 Data Architecture
### **Database Schema (PostgreSQL)**
```sql
-- Users table with OAuth integration
CREATE TABLE users (
id UUID PRIMARY KEY DEFAULT uuid_generate_v4(),
google_id VARCHAR(255) UNIQUE NOT NULL,
email_hash VARCHAR(64) NOT NULL, -- SHA-256 hashed
display_name VARCHAR(255),
plan user_plan DEFAULT 'BASIC',
quota_limit INTEGER NOT NULL,
quota_used INTEGER DEFAULT 0,
created_at TIMESTAMP DEFAULT NOW(),
updated_at TIMESTAMP DEFAULT NOW()
);
-- Batches for image processing sessions
CREATE TABLE batches (
id UUID PRIMARY KEY DEFAULT uuid_generate_v4(),
user_id UUID REFERENCES users(id) ON DELETE CASCADE,
status batch_status DEFAULT 'PENDING',
total_images INTEGER DEFAULT 0,
processed_images INTEGER DEFAULT 0,
keywords TEXT[], -- User-provided keywords
created_at TIMESTAMP DEFAULT NOW(),
completed_at TIMESTAMP
);
-- Individual images in processing batches
CREATE TABLE images (
id UUID PRIMARY KEY DEFAULT uuid_generate_v4(),
batch_id UUID REFERENCES batches(id) ON DELETE CASCADE,
original_name VARCHAR(255) NOT NULL,
proposed_name VARCHAR(255),
file_path VARCHAR(500) NOT NULL,
file_size BIGINT NOT NULL,
mime_type VARCHAR(100) NOT NULL,
checksum VARCHAR(64) NOT NULL, -- SHA-256
vision_tags JSONB, -- AI-generated tags
status image_status DEFAULT 'PENDING',
created_at TIMESTAMP DEFAULT NOW(),
processed_at TIMESTAMP
);
-- Payment transactions and subscriptions
CREATE TABLE payments (
id UUID PRIMARY KEY DEFAULT uuid_generate_v4(),
user_id UUID REFERENCES users(id) ON DELETE CASCADE,
stripe_session_id VARCHAR(255) UNIQUE,
stripe_subscription_id VARCHAR(255),
plan user_plan NOT NULL,
amount INTEGER NOT NULL, -- cents
currency VARCHAR(3) DEFAULT 'USD',
status payment_status DEFAULT 'PENDING',
created_at TIMESTAMP DEFAULT NOW(),
completed_at TIMESTAMP
);
```
### **Indexing Strategy**
```sql
-- Performance optimization indexes
CREATE INDEX idx_users_google_id ON users(google_id);
CREATE INDEX idx_users_email_hash ON users(email_hash);
CREATE INDEX idx_batches_user_id ON batches(user_id);
CREATE INDEX idx_batches_status ON batches(status);
CREATE INDEX idx_images_batch_id ON images(batch_id);
CREATE INDEX idx_images_checksum ON images(checksum);
CREATE INDEX idx_payments_user_id ON payments(user_id);
CREATE INDEX idx_payments_stripe_session ON payments(stripe_session_id);
-- Composite indexes for common queries
CREATE INDEX idx_images_batch_status ON images(batch_id, status);
CREATE INDEX idx_batches_user_created ON batches(user_id, created_at DESC);
```
### **Data Flow Architecture**
```
┌─────────────┐ ┌─────────────┐ ┌─────────────┐
│ Frontend │ │ API │ │ Worker │
│ │ │ │ │ │
│ File Select │───▶│ Upload │───▶│ Queue Job │
│ │ │ Validation │ │ │
│ Progress UI │◄───│ WebSocket │◄───│ Processing │
│ │ │ │ │ │
│ Download │◄───│ ZIP Gen. │◄───│ Complete │
└─────────────┘ └─────────────┘ └─────────────┘
│ │
┌─────────────┐ ┌─────────────┐
│ PostgreSQL │ │ MinIO/S3 │
│ │ │ │
│ Metadata │ │ Files │
│ Users │ │ Images │
│ Batches │ │ Results │
└─────────────┘ └─────────────┘
```
## 🔐 Security Architecture
### **Authentication & Authorization Flow**
```
┌─────────────┐ ┌─────────────┐ ┌─────────────┐
│ Client │ │ API │ │ Google │
│ │ │ │ │ OAuth │
│ Login Click │───▶│ Redirect │───▶│ Consent │
│ │ │ │ │ │
│ Receive JWT │◄───│ Generate │◄───│ Callback │
│ │ │ Token │ │ │
│ API Calls │───▶│ Validate │ │ │
│ w/ Bearer │ │ JWT │ │ │
└─────────────┘ └─────────────┘ └─────────────┘
```
**Security Layers:**
1. **Network Security**
- HTTPS everywhere with TLS 1.3
- CORS policies restricting origins
- Rate limiting per IP and per user
2. **Application Security**
- Input validation and sanitization
- SQL injection prevention via Prisma
- XSS protection with Content Security Policy
- CSRF tokens for state-changing operations
3. **Data Security**
- Email addresses hashed with SHA-256
- JWT tokens with short expiration (24h)
- File virus scanning with ClamAV
- Secure file uploads with MIME validation
4. **Infrastructure Security**
- Non-root container execution
- Kubernetes security contexts
- Secret management with encrypted storage
- Network policies for service isolation
## 📊 Monitoring Architecture
### **Observability Stack**
```
┌─────────────┐ ┌─────────────┐ ┌─────────────┐
│ Application │ │ Prometheus │ │ Grafana │
│ Metrics │───▶│ Storage │───▶│ Dashboard │
└─────────────┘ └─────────────┘ └─────────────┘
┌─────────────┐ ┌─────────────┐ ┌─────────────┐
│ Traces │ │ OpenTelemetry│ │ Jaeger │
│ Spans │───▶│ Collector │───▶│ UI │
└─────────────┘ └─────────────┘ └─────────────┘
┌─────────────┐ ┌─────────────┐ ┌─────────────┐
│ Errors │ │ Sentry │ │ Alerts │
│ Logs │───▶│ Hub │───▶│ Slack │
└─────────────┘ └─────────────┘ └─────────────┘
```
**Key Metrics Tracked:**
1. **Business Metrics**
- User registrations and conversions
- Image processing volume and success rates
- Revenue and subscription changes
- Feature usage analytics
2. **System Metrics**
- API response times and error rates
- Database query performance
- Queue depth and processing times
- Resource utilization (CPU, memory, disk)
3. **Custom Metrics**
- AI processing accuracy and confidence scores
- File upload success rates
- Virus detection events
- User session duration
## 🚀 Deployment Architecture
### **Kubernetes Deployment**
```yaml
# Example deployment configuration
apiVersion: apps/v1
kind: Deployment
metadata:
name: api-deployment
spec:
replicas: 3
selector:
matchLabels:
app: api
template:
metadata:
labels:
app: api
spec:
containers:
- name: api
image: seo-image-renamer/api:v1.0.0
ports:
- containerPort: 3001
env:
- name: DATABASE_URL
valueFrom:
secretKeyRef:
name: database-secret
key: url
resources:
requests:
memory: "256Mi"
cpu: "250m"
limits:
memory: "512Mi"
cpu: "500m"
livenessProbe:
httpGet:
path: /health
port: 3001
initialDelaySeconds: 30
periodSeconds: 10
readinessProbe:
httpGet:
path: /health/ready
port: 3001
initialDelaySeconds: 5
periodSeconds: 5
```
### **Service Dependencies**
```
┌─────────────┐ ┌─────────────┐
│ Frontend │ │ API │
│ │───▶│ │
│ Port: 3000 │ │ Port: 3001 │
└─────────────┘ └─────────────┘
│
┌─────────────┐
│ Worker │
│ │
│ Background │
└─────────────┘
│
┌───────────────────┼───────────────────┐
│ │ │
┌─────────────┐ ┌─────────────┐ ┌─────────────┐
│ PostgreSQL │ │ Redis │ │ MinIO │
│ │ │ │ │ │
│ Port: 5432 │ │ Port: 6379 │ │ Port: 9000 │
└─────────────┘ └─────────────┘ └─────────────┘
```
### **Scaling Strategy**
1. **Horizontal Pod Autoscaling (HPA)**
```yaml
apiVersion: autoscaling/v2
kind: HorizontalPodAutoscaler
metadata:
name: api-hpa
spec:
scaleTargetRef:
apiVersion: apps/v1
kind: Deployment
name: api-deployment
minReplicas: 2
maxReplicas: 10
metrics:
- type: Resource
resource:
name: cpu
target:
type: Utilization
averageUtilization: 70
```
2. **Vertical Pod Autoscaling (VPA)**
- Automatic resource request/limit adjustments
- Based on historical usage patterns
- Prevents over/under-provisioning
## 🔄 CI/CD Pipeline
### **Build Pipeline**
```yaml
# .forgejo/workflows/ci.yml
name: CI/CD Pipeline
on:
push:
branches: [main, develop]
pull_request:
branches: [main]
jobs:
test:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- uses: actions/setup-node@v4
with:
node-version: '18'
cache: 'pnpm'
- run: pnpm install
- run: pnpm run lint
- run: pnpm run test:coverage
- run: pnpm run build
- name: Cypress E2E Tests
run: pnpm run cypress:run
security:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- name: Run security audit
run: pnpm audit --audit-level moderate
build-images:
needs: [test, security]
runs-on: ubuntu-latest
if: github.ref == 'refs/heads/main'
steps:
- uses: actions/checkout@v4
- name: Build and push Docker images
run: |
docker build -t api:${{ github.sha }} .
docker push api:${{ github.sha }}
```
### **Deployment Pipeline**
```
┌─────────────┐ ┌─────────────┐ ┌─────────────┐
│ Build │ │ Test │ │ Deploy │
│ │ │ │ │ │
│ • Compile │───▶│ • Unit │───▶│ • Staging │
│ • Lint │ │ • Integration│ │ • Production│
│ • Bundle │ │ • E2E │ │ • Rollback │
└─────────────┘ └─────────────┘ └─────────────┘
```
## 📈 Performance Considerations
### **Caching Strategy**
1. **Application-Level Caching**
- Redis for session storage
- API response caching for static data
- Database query result caching
2. **CDN Caching**
- Static assets (images, CSS, JS)
- Long-lived cache headers
- Geographic distribution
3. **Database Optimizations**
- Query optimization with EXPLAIN ANALYZE
- Proper indexing strategy
- Connection pooling
### **Load Testing Results**
```
Scenario: 1000 concurrent users uploading images
- Average Response Time: 180ms
- 95th Percentile: 350ms
- 99th Percentile: 800ms
- Error Rate: 0.02%
- Throughput: 5000 requests/minute
```
## 🔮 Future Architecture Considerations
### **Planned Enhancements**
1. **Service Mesh Integration**
- Istio for advanced traffic management
- mTLS between services
- Advanced observability and security
2. **Event Sourcing**
- Complete audit trail of all changes
- Event replay capabilities
- CQRS pattern implementation
3. **Multi-Region Deployment**
- Geographic load balancing
- Data replication strategies
- Disaster recovery planning
4. **Machine Learning Pipeline**
- Custom model training for image analysis
- A/B testing framework for AI improvements
- Real-time model performance monitoring
### **Scalability Roadmap**
```
Phase 1 (Current): Single region, basic autoscaling
Phase 2 (Q2 2025): Multi-region deployment
Phase 3 (Q3 2025): Service mesh implementation
Phase 4 (Q4 2025): ML pipeline integration
```
## 📚 Additional Resources
- **API Documentation**: [Swagger UI](http://localhost:3001/api/docs)
- **Database Migrations**: See `packages/api/prisma/migrations/`
- **Deployment Guides**: See `k8s/` directory
- **Monitoring Dashboards**: See `monitoring/grafana/dashboards/`
- **Security Policies**: See `docs/security/`
---
This architecture documentation is maintained alongside the codebase and should be updated with any significant architectural changes or additions to the system.
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