YeboLearn Architecture: Built for Africa, Scaled for the World
Executive Summary
YeboLearn's architecture isn't just modern—it's future-proof. Built on cloud-native principles with multi-tenant isolation, microservices architecture, and AI-first design, we deliver enterprise-grade reliability at startup speed. While competitors struggle with monolithic legacy systems, we scale infinitely, deploy instantly, and innovate continuously.
System Architecture Overview
┌─────────────────────────────────────────────────────────────┐
│ CLIENTS │
├──────────────┬──────────────┬──────────────┬──────────────┤
│ Web (PWA) │ Mobile (PWA) │ API Clients │ Integrations │
└──────┬───────┴──────┬───────┴──────┬───────┴──────┬───────┘
│ │ │ │
┌──────▼──────────────▼──────────────▼──────────────▼───────┐
│ CDN (Cloudflare) │
│ Static Assets + DDoS Protection │
└──────────────────────┬─────────────────────────────────────┘
│
┌──────────────────────▼─────────────────────────────────────┐
│ LOAD BALANCER (GCP) │
└──────┬────────────────────────────────────┬────────────────┘
│ │
┌──────▼──────────────────────┐ ┌──────────▼────────────────┐
│ API GATEWAY │ │ WebSocket Server │
│ (Kong / Express.js) │ │ (Socket.io) │
└──────┬──────────────────────┘ └──────────┬────────────────┘
│ │
┌──────▼────────────────────────────────────▼────────────────┐
│ MICROSERVICES LAYER │
├──────────────┬──────────────┬──────────────┬──────────────┤
│ Core API │ AI Service │ Payment Svc │ Notification │
│ (Node.js) │ (Python) │ (Node.js) │ (Node.js) │
└──────┬───────┴──────┬───────┴──────┬───────┴──────┬───────┘
│ │ │ │
┌──────▼──────────────▼──────────────▼──────────────▼───────┐
│ DATA LAYER │
├─────────────┬─────────────┬─────────────┬─────────────────┤
│ PostgreSQL │ Redis │ S3/GCS │ Elasticsearch │
│ (Primary) │ (Cache) │ (Storage) │ (Search) │
└─────────────┴─────────────┴─────────────┴─────────────────┘Multi-Tenant Architecture
Tenant Isolation Strategy
Database Level Isolation
-- Schema-based multi-tenancy
CREATE SCHEMA tenant_001;
CREATE SCHEMA tenant_002;
-- Row-level security
ALTER TABLE students ENABLE ROW LEVEL SECURITY;
CREATE POLICY tenant_isolation ON students
USING (tenant_id = current_setting('app.tenant_id'));Why Schema-Based Multi-Tenancy?
- Complete data isolation between schools
- Easy backup/restore per tenant
- Performance optimization per school size
- Compliance ready for data residency
- Cost efficient versus separate databases
Tenant Provisioning Flow
- Sign-up: New school registers
- Provisioning: Automated schema creation (<30 seconds)
- Configuration: School-specific settings applied
- Data Seeding: Default data populated
- Activation: School ready for use
Scaling Strategy
- Small Schools (<500 students): Shared infrastructure
- Medium Schools (500-5000): Dedicated resources
- Large Schools (5000+): Isolated deployment
- Enterprise (Multi-school): Private cloud option
Microservices Architecture
Service Decomposition
Core API Service
Technology: Node.js 18+, Express.js, TypeScript Responsibilities:
- Student management
- Academic operations
- Attendance tracking
- Basic CRUD operations
- Business logic
Why Node.js:
- Non-blocking I/O perfect for concurrent requests
- JavaScript everywhere (frontend + backend)
- Massive ecosystem
- Fast development cycle
AI Service
Technology: Python, FastAPI, Google Gemini Responsibilities:
- Natural language processing
- Predictive analytics
- Content generation
- Image recognition
- ML model serving
Why Python:
- Best AI/ML libraries
- Google Gemini SDK
- Data science ecosystem
- Easy model deployment
Payment Service
Technology: Node.js, Stripe SDK, MTN API Responsibilities:
- Payment processing
- Reconciliation
- Refund management
- Payment gateway abstraction
- PCI compliance
Isolation Benefits:
- PCI compliance scope reduction
- Independent scaling
- Provider-specific optimizations
- Fault isolation
Notification Service
Technology: Node.js, Bull Queue, Twilio Responsibilities:
- Email delivery
- SMS dispatch
- Push notifications
- WhatsApp messages
- Delivery tracking
Queue-Based Architecture:
// Reliable message delivery
await notificationQueue.add('send-sms', {
to: parentPhone,
message: 'Your child is absent today',
priority: 'high',
retry: 3
});Service Communication
Synchronous: REST APIs
// Internal service calls
const studentData = await coreAPI.get('/students/123');
const aiInsights = await aiService.post('/analyze', studentData);Asynchronous: Message Queue
// Event-driven architecture
eventBus.publish('student.enrolled', {
studentId: 123,
schoolId: 456,
timestamp: Date.now()
});Real-time: WebSockets
// Live updates
socket.emit('attendance.marked', {
studentId: 123,
status: 'present'
});Infrastructure Architecture
Container Orchestration
Docker Containerization
# Optimized multi-stage build
FROM node:18-alpine AS builder
WORKDIR /app
COPY package*.json ./
RUN npm ci --only=production
FROM node:18-alpine
WORKDIR /app
COPY --from=builder /app/node_modules ./node_modules
COPY . .
EXPOSE 3000
CMD ["node", "server.js"]Google Cloud Run Deployment
Why Cloud Run:
- Serverless containers
- Automatic scaling (0 to 1000 instances)
- Pay per request
- Built-in load balancing
- Zero DevOps overhead
Scaling Configuration:
apiVersion: serving.knative.dev/v1
kind: Service
metadata:
name: yebolearn-api
spec:
template:
metadata:
annotations:
run.googleapis.com/execution-environment: gen2
autoscaling.knative.dev/minScale: "2"
autoscaling.knative.dev/maxScale: "1000"
spec:
containerConcurrency: 1000
timeoutSeconds: 300Database Architecture
PostgreSQL 15 Configuration
-- Performance optimizations
max_connections = 200
shared_buffers = 4GB
effective_cache_size = 12GB
work_mem = 20MB
maintenance_work_mem = 1GB
-- Multi-tenant optimizations
max_locks_per_transaction = 256
max_pred_locks_per_transaction = 256Connection Pooling
// PgBouncer configuration
const pool = new Pool({
max: 20, // per service
idleTimeoutMillis: 30000,
connectionTimeoutMillis: 2000,
});Read Replica Strategy
- Primary: All writes
- Replica 1: Reporting queries
- Replica 2: Analytics workloads
- Replica 3: Backup and disaster recovery
Caching Architecture
Redis 7 Implementation
// Multi-tier caching
const cacheStrategy = {
L1: 'Application Memory (30s)', // Hot data
L2: 'Redis (5 min)', // Frequent queries
L3: 'Database', // Source of truth
};Cache Patterns
// Cache-aside pattern
async function getStudent(id) {
// Check cache first
let student = await redis.get(`student:${id}`);
if (!student) {
// Cache miss - fetch from DB
student = await db.query('SELECT * FROM students WHERE id = $1', [id]);
await redis.setex(`student:${id}`, 300, JSON.stringify(student));
}
return student;
}Security Architecture
Defense in Depth
Layer 1: CDN/WAF (Cloudflare)
- DDoS protection
- Bot mitigation
- Rate limiting
- Geo-blocking
- SSL/TLS termination
Layer 2: API Gateway
- Authentication (JWT)
- Authorization (RBAC)
- Request validation
- API versioning
- Throttling
Layer 3: Application
- Input sanitization
- SQL injection prevention
- XSS protection
- CSRF tokens
- Content Security Policy
Layer 4: Database
- Encrypted at rest
- Encrypted in transit
- Row-level security
- Audit logging
- Backup encryption
Authentication & Authorization
JWT Implementation
// Token structure
{
"sub": "user_123",
"tenant": "school_456",
"role": "teacher",
"permissions": ["read:students", "write:grades"],
"exp": 1234567890
}RBAC Model
const roles = {
superAdmin: ['*'],
schoolAdmin: ['manage:school', 'view:all'],
teacher: ['manage:class', 'view:students'],
parent: ['view:child'],
student: ['view:self']
};Performance Architecture
Optimization Strategies
API Response Optimization
// GraphQL for precise data fetching
const query = `
query GetStudent($id: ID!) {
student(id: $id) {
name
grades { subject score }
}
}
`;Database Query Optimization
-- Optimized indexes
CREATE INDEX idx_students_school_class
ON students(tenant_id, school_id, class_id);
-- Materialized views for reports
CREATE MATERIALIZED VIEW daily_attendance_summary AS
SELECT date, class_id, COUNT(*) as present
FROM attendance
WHERE status = 'present'
GROUP BY date, class_id;Frontend Optimization
- Code splitting by route
- Lazy loading components
- Image optimization (WebP)
- Service worker caching
- CDN for static assets
Performance Metrics
Target SLAs
| Metric | Target | Current | Industry Average |
|---|---|---|---|
| API Response Time | <200ms | 145ms | 500ms |
| Page Load Time | <2s | 1.3s | 4s |
| Database Query | <100ms | 67ms | 250ms |
| Uptime | 99.9% | 99.95% | 99% |
| Error Rate | <0.1% | 0.03% | 1% |
Scalability Architecture
Horizontal Scaling
Auto-scaling Rules
# CPU-based scaling
- metricType: cpu
targetUtilization: 70
# Request-based scaling
- metricType: request-count
targetValue: 100
# Custom metrics
- metricType: queue-depth
targetValue: 50Vertical Scaling
- Database: Up to 64 vCPUs, 256GB RAM
- Cache: Up to 100GB Redis cluster
- Storage: Unlimited object storage
- Compute: Serverless (infinite)
Geographic Distribution
Primary Region: South Africa (Johannesburg)
├── CDN PoPs: 200+ global locations
├── Backup Region: Europe (Frankfurt)
└── Disaster Recovery: US (Virginia)Monitoring & Observability
Monitoring Stack
Metrics: Prometheus + Grafana
Logs: ELK Stack (Elasticsearch, Logstash, Kibana)
Traces: Jaeger
APM: New Relic
Uptime: StatusPageKey Metrics Tracked
- Request rate and latency
- Error rates by endpoint
- Database connection pool
- Cache hit/miss ratio
- Queue depth and processing time
- AI model inference time
- Payment success rate
Alerting Rules
- name: High Error Rate
condition: error_rate > 1%
action: page_oncall
- name: Database Connection Pool
condition: available_connections < 10
action: scale_database
- name: API Latency
condition: p95_latency > 500ms
action: investigateDisaster Recovery
Backup Strategy
- Database: Continuous replication + hourly snapshots
- Files: Real-time S3 sync with versioning
- Code: Git with automated deployments
- Configuration: Encrypted in version control
Recovery Objectives
- RTO (Recovery Time): <1 hour
- RPO (Recovery Point): <15 minutes
- Backup Retention: 90 days
- Disaster Recovery Test: Monthly
Competitive Architecture Advantages
| Aspect | YeboLearn | Typical Competitor |
|---|---|---|
| Architecture | Microservices | Monolithic |
| Deployment | Serverless/Containers | VMs/Bare metal |
| Scaling | Auto-scaling | Manual |
| Multi-tenancy | Schema isolation | Shared tables |
| Database | PostgreSQL 15 | MySQL 5.7 |
| Caching | Redis cluster | None/Basic |
| Message Queue | RabbitMQ/Redis | None |
| API Design | RESTful + GraphQL | SOAP/Basic REST |
| Monitoring | Full observability | Basic logging |
| Security | Defense in depth | Perimeter only |
Architecture Evolution Roadmap
2025 Q1-Q2
- GraphQL federation
- Event sourcing for audit
- CQRS implementation
- Edge computing capabilities
2025 Q3-Q4
- Kubernetes migration
- Service mesh (Istio)
- Distributed tracing
- Global multi-region
2026
- Blockchain integration
- Federated learning
- Edge AI inference
- Quantum-ready encryption
The Architecture Advantage
YeboLearn's architecture isn't just technically superior—it's business transformative. While competitors struggle with:
- Monolithic complexity: We deploy features in minutes
- Scaling bottlenecks: We scale infinitely
- Security vulnerabilities: We implement defense in depth
- Performance issues: We deliver sub-second responses
- Maintenance nightmares: We achieve 99.95% uptime
Key Takeaway
YeboLearn is built on the same architecture principles as Netflix, Uber, and Airbnb—proven patterns that scale to millions of users. But unlike Silicon Valley companies, we've optimized specifically for African conditions: low bandwidth, mobile-first, offline-capable, and cost-efficient.
This isn't just good architecture—it's the only architecture that can deliver on Africa's educational transformation.