Technical Architecture
Building a high-performance, blockchain-powered prediction platform at scale
Technology Stack Overview
Architecture Philosophy
Hybrid Model: Speed + Transparency
Traditional database for performance-critical operations (real-time predictions, odds calculation)
Blockchain for transparency and immutability (prediction receipts, settlement proofs, audit trail)
Frontend Stack
Web Application
- Framework: Next.js 14 (React)
- Language: TypeScript
- State Management: Zustand + React Query
- Styling: Tailwind CSS + Shadcn/ui
- Charts: ApexCharts, Recharts
- Real-time: WebSockets (Socket.io)
Mobile Apps
- Framework: React Native (Expo)
- Platform: iOS & Android
- Notifications: Firebase Cloud Messaging
- Biometrics: Face ID / Fingerprint
- Offline Mode: Async Storage
Web3 Integration
- Wallet Connect: WalletConnect v2
- Web3 Library: Ethers.js v6
- Wallet Support: MetaMask, Trust, Coinbase
- Chain Support: Polygon, Ethereum
Performance Optimization
- CDN: Cloudflare (global edge caching)
- Image Optimization: Next.js Image, WebP
- Code Splitting: Dynamic imports
- SSR/SSG: Server-side rendering for SEO
Backend Architecture
Microservices Design
Why Microservices? Independent scaling, fault isolation, language flexibility
Each service handles a specific domain with its own database and API
Core Services
| Service | Technology | Responsibility | Scale Requirements |
|---|---|---|---|
| API Gateway | Node.js + Express | Route requests, auth, rate limiting | 10k+ req/sec |
| Prediction Engine | Rust | Process predictions, calculate odds, settlements | Critical (sub-100ms latency) |
| User Service | Node.js + TypeScript | Auth, profiles, KYC, preferences | Medium load |
| Blockchain Service | Node.js + Ethers.js | Write to blockchain, receipt generation | Async queue-based |
| Payment Service | Node.js + TypeScript | Deposits, withdrawals, fiat/crypto | High reliability required |
| Price Feed Service | Python + FastAPI | Aggregate price data, normalize feeds | Real-time streaming |
| Analytics Service | Python + Pandas | User stats, win rates, insights | Batch processing |
| Notification Service | Node.js + Bull Queue | Email, SMS, push notifications | Queue-based async |
| Gamification Service | Node.js + TypeScript | Badges, seasons, leaderboards | Medium load |
| Compliance Service | Python + FastAPI | KYC, AML, geo-blocking, risk scoring | Critical for legal compliance |
Why Rust for Prediction Engine?
- Performance: 10-100x faster than Node.js for CPU-intensive tasks
- Memory Safety: No runtime errors, guaranteed thread safety
- Reliability: Financial calculations require absolute precision
- Concurrency: Handle thousands of simultaneous predictions without bottlenecks
Database Architecture
Multi-Database Strategy
Different data types require different storage solutions:
PostgreSQL (Primary)
Use Case: Transactional data, user accounts, predictions
- ACID compliance for financial data
- Complex queries and joins
- Partitioning for historical data
- Read replicas for scaling
Redis (Caching + Real-time)
Use Case: Session data, live odds, hot data
- Sub-millisecond read times
- Pub/Sub for WebSocket events
- Leaderboard sorted sets
- Rate limiting counters
TimescaleDB
Use Case: Price history at "9" timestamps
- Optimized for time-series data
- Store only :09, :19, :29, etc. prices
- Infinite historical lookback
- Fast aggregation queries
MongoDB
Use Case: Logs, events, unstructured data
- Flexible schema for analytics
- Document-based prediction receipts
- Audit trail storage
- Fast writes for logging
Data Retention Strategy
| Data Type | Hot Storage | Cold Storage | Blockchain |
|---|---|---|---|
| Active predictions | PostgreSQL + Redis | - | - |
| Settled predictions (30 days) | PostgreSQL | - | Receipt hash |
| Settled predictions (30+ days) | - | S3 Glacier | Receipt hash |
| Price data (all "9" timestamps) | TimescaleDB | S3 + TimescaleDB archive | Merkle root daily |
| User analytics | MongoDB | S3 Parquet | - |
Blockchain Integration (Polygon)
Why Polygon Layer 2?
Cost Comparison
- Ethereum L1: $1.58 per transaction
- Polygon L2: $0.0009 per transaction
- At 1M predictions/day: Save $1.57M daily
Performance
- Confirmation Time: 2.1 seconds
- Throughput: 71.2 TPS
- Finality: Probabilistic (safe after 128 blocks)
Smart Contracts Architecture
Core Contracts (Solidity 0.8.20+)
PredictionVault.sol
Purpose: Hold user funds, process payouts
- Multi-sig wallet (3 of 5 keys)
- Automated payout execution
- Emergency pause functionality
- Upgradeable proxy pattern
PredictionReceipt.sol
Purpose: Immutable prediction records
- Store prediction hash on-chain
- Timestamp, asset, direction, amount
- Settlement price and result
- Provably fair verification
PriceOracle.sol
Purpose: Decentralized price feeds
- Chainlink integration
- Fallback to multiple oracles
- Median price calculation
- Dispute resolution mechanism
NFTBadges.sol
Purpose: Achievement NFTs
- ERC-721 standard
- Soulbound (non-transferable)
- Dynamic metadata (SVG on-chain)
- Rarity tiers and levels
Transaction Flow
1. User Makes Prediction (Off-Chain)
Prediction stored in PostgreSQL, instant confirmation
User experience: <1 second response
2. Prediction Queued for Blockchain
Redis queue with prediction hash
Batched with other predictions (gas optimization)
3. Blockchain Write (Async)
Smart contract writes receipt hash
~2 seconds confirmation
4. Settlement at :X9
Price oracle provides settlement price
Smart contract validates and executes payout
5. Receipt Updated
Blockchain receipt includes final result
User can verify on Polygonscan
Gas Optimization Strategies
- Batch Processing: Group 100+ predictions per transaction (save 95% gas)
- Merkle Proofs: Store root hash on-chain, details off-chain
- Event Logs: Use events instead of storage for historical data
- Minimal Storage: Only essential data on-chain (hashes, not full details)
NFT Integration: Badges & Collectibles
NFT-Powered Gamification
Blockchain badges = Provably rare, tradeable achievements
Unlike traditional gaming achievements, TheSixNines badges are:
- Owned by the user (not the platform)
- Verifiably rare (blockchain proves only X exist)
- Tradeable on secondary markets (OpenSea, etc.)
- Cross-platform compatible (show off in other apps)
NFT Types
Achievement Badges (Soulbound)
Non-transferable, permanent achievements
- First Win badge
- 100 Wins badge
- Hot Streak (10+ wins in a row)
- Legendary (1000+ wins)
These cannot be sold or transferred - prove YOUR skill
Special Moment NFTs (Tradeable)
Collectible, limited edition
- $420.69 wins (capped at 420 total)
- $69.69 wins (capped at 6,969 total)
- Perfect timing wins (prediction placed <5s before cutoff)
- Season champion badges
Tradeable on OpenSea, have resale value
VIP Membership NFTs
Access pass with utility
- Diamond VIP: 0% fees for life
- Gold VIP: 50% fee reduction
- Early access to new features
- Exclusive Discord channels
Limited supply, appreciates with platform growth
Dynamic NFTs (Evolving)
Metadata changes based on performance
- Level up based on total wins
- Visual changes (bronze → gold → diamond)
- Stats embedded in NFT metadata
- Win rate displayed on badge
NFT "grows" with your skill
Revenue from NFTs
| NFT Type | Mint Price | Supply | Royalty | Revenue Potential |
|---|---|---|---|---|
| $420.69 Win NFT | Free (earned) | 420 max | 5% royalty | Secondary market volume |
| Diamond VIP Pass | $5,000 | 1,000 max | 10% royalty | $5M + ongoing royalties |
| Season Champion | Free (earned) | 1 per season | 10% royalty | High collector value |
| Founder Badge | Free (first 1,000 users) | 1,000 max | 5% royalty | Community building |
Smart Contract Example: Dynamic Badge
// Dynamic NFT that levels up based on wins
contract DynamicBadge is ERC721 {
struct Badge {
uint256 wins;
uint256 level;
uint256 lastUpdated;
}
mapping(uint256 => Badge) public badges;
function updateWins(uint256 tokenId, uint256 newWins) external {
badges[tokenId].wins = newWins;
badges[tokenId].level = calculateLevel(newWins);
badges[tokenId].lastUpdated = block.timestamp;
}
function tokenURI(uint256 tokenId) public view returns (string memory) {
// Generate SVG based on current level
return generateDynamicSVG(badges[tokenId]);
}
}
Real-Time Data Infrastructure
Price Feed Aggregation
Primary Sources
- Stocks: Polygon.io, Alpaca Data API
- Crypto: Binance, Coinbase, Kraken
- Backup: Yahoo Finance, IEX Cloud
Aggregation Logic
- Pull from 3+ sources simultaneously
- Calculate median price (outlier resistant)
- Discard prices >0.1% from median
- Store at :09, :19, :29, :39, :49, :59 only
WebSocket Architecture
- Socket.io Server: Handles 100k+ concurrent connections
- Redis Pub/Sub: Distribute messages across server instances
- Room-Based: Users subscribe to specific assets (SPY, BTC, etc.)
- Heartbeat: Ping every 30s to detect disconnects
- Reconnection: Automatic with exponential backoff
Event Stream
| Event Type | Frequency | Data Sent |
|---|---|---|
| Price Update | Every 1 second | Current price, change %, timestamp |
| Countdown Timer | Every 1 second | Seconds until next settlement |
| Prediction Made | Real-time | Anonymous prediction (direction, asset, count) |
| Settlement | Every 10 minutes | Final price, results, payouts |
| Leaderboard Update | Every 5 minutes | Top 10 rankings |
Security Architecture
Multi-Layer Security
1. Infrastructure Security
- AWS VPC with private subnets
- WAF (Web Application Firewall)
- DDoS protection (Cloudflare + AWS Shield)
- Encrypted at rest (AES-256)
- Encrypted in transit (TLS 1.3)
2. Application Security
- Rate limiting (Redis-based)
- Input sanitization (all user data)
- SQL injection prevention (parameterized queries)
- XSS protection (Content Security Policy)
- CSRF tokens on all forms
3. Smart Contract Security
- Audited by CertiK, OpenZeppelin
- Formal verification (critical functions)
- Multi-sig wallet (3 of 5 keys)
- Time-locked upgrades (48h delay)
- Emergency pause capability
4. Financial Security
- Hot wallet: <5% of funds
- Cold storage: 95% in hardware wallets
- Insurance: $10M coverage (Nexus Mutual)
- Withdrawal limits: $10k/day (adjustable)
- 2FA required for all withdrawals
Compliance & Monitoring
- KYC/AML: Onfido + Chainalysis integration
- Geo-blocking: MaxMind GeoIP + VPN detection
- Transaction Monitoring: Flag suspicious patterns (Chainalysis)
- Audit Logs: Every action logged (immutable)
- Penetration Testing: Quarterly by third-party firms
DevOps & Infrastructure
Cloud Architecture (AWS)
| Component | Service | Configuration |
|---|---|---|
| Compute | ECS Fargate | Auto-scaling, containerized microservices |
| Load Balancer | ALB | Multi-AZ, health checks, SSL termination |
| Database | RDS PostgreSQL | Multi-AZ, automated backups, read replicas |
| Cache | ElastiCache Redis | Cluster mode, auto-failover |
| Object Storage | S3 | Versioning, lifecycle policies, Glacier archive |
| CDN | CloudFront + Cloudflare | Global edge locations, DDoS protection |
| Monitoring | CloudWatch + Datadog | Metrics, logs, traces, alerts |
| CI/CD | GitHub Actions | Automated testing, deployment pipelines |
Deployment Strategy
- Blue-Green Deployments: Zero downtime updates
- Canary Releases: 5% traffic to new version, monitor, then 100%
- Rollback: Instant rollback to previous version if errors spike
- Feature Flags: LaunchDarkly for gradual feature rollout
Monitoring & Observability
Metrics
- Response times (p50, p95, p99)
- Error rates by endpoint
- Database query performance
- Blockchain confirmation times
Logging
- Structured JSON logs
- Centralized (CloudWatch Logs)
- Request tracing (trace ID)
- Sensitive data redaction
Alerts
- Error rate >1%: Page on-call engineer
- API latency >500ms: Slack alert
- Blockchain queue >1000: Auto-scale
- Anomaly detection: ML-based alerts
Distributed Tracing
- OpenTelemetry instrumentation
- Trace requests across microservices
- Identify bottlenecks
- Visualize service dependencies
API Design
RESTful + GraphQL Hybrid
REST API (Public)
Simple, cacheable endpoints for common operations
- GET /api/v1/assets
- GET /api/v1/prices/:asset
- POST /api/v1/predictions
- GET /api/v1/user/bets
GraphQL (Advanced)
Complex queries, fetch exactly what you need
- User dashboard (single query, all data)
- Analytics (custom aggregations)
- Leaderboards (paginated, filtered)
- Real-time subscriptions
API Performance
- Caching: Redis for hot data (99% cache hit rate goal)
- Pagination: Cursor-based for large datasets
- Compression: Gzip/Brotli for responses
- Rate Limiting: 1000 req/min per user (adjustable per tier)
Testing Strategy
Multi-Level Testing
| Test Type | Coverage Goal | Tools | Frequency |
|---|---|---|---|
| Unit Tests | 80% | Jest, Mocha, Pytest | Every commit |
| Integration Tests | Critical paths | Supertest, Postman | Every PR |
| E2E Tests | User flows | Playwright, Cypress | Pre-deployment |
| Load Tests | 10k concurrent users | k6, Artillery | Weekly |
| Security Tests | OWASP Top 10 | OWASP ZAP, Burp Suite | Monthly |
| Smart Contract Audits | 100% coverage | Hardhat, Foundry | Before deployment |
Chaos Engineering
Deliberately break things to test resilience:
- Kill random database connections (test retry logic)
- Simulate network latency (test timeout handling)
- Corrupt Redis cache (test fallback to DB)
- Blockchain RPC failures (test oracle fallbacks)
Scalability Roadmap
Scaling to 1 Million Users
| Milestone | Users | Infrastructure Changes | Cost |
|---|---|---|---|
| MVP (Month 1-6) | 5,000 | Single region, 4 ECS tasks, 1 DB | $2k/month |
| Scale (Month 7-12) | 50,000 | Multi-AZ, 20 ECS tasks, read replicas | $15k/month |
| Growth (Year 2) | 200,000 | Multi-region, 100 ECS tasks, sharded DB | $80k/month |
| Massive (Year 3) | 1,000,000 | Global edge, 500+ ECS tasks, distributed DB | $400k/month |
Note: At 1M users generating $1.5B annual revenue, infrastructure is <0.3% of revenue
Database Sharding Strategy
- Shard Key: User ID (ensures user data on same shard)
- Shard Count: Start with 4, grow to 16, then 64
- Rebalancing: Automated with minimal downtime
- Cross-Shard Queries: Federated via API layer
Why This Stack Wins
🚀 Performance
Rust prediction engine = sub-100ms prediction processing
Redis caching = <10ms API responses
CDN = <50ms page loads globally
🔒 Security
Multi-sig wallets = No single point of failure
Audited contracts = Funds are safe
Insurance = $10M coverage
📈 Scalability
Microservices = Scale each component independently
Auto-scaling = Handle traffic spikes
Multi-region = Low latency globally
💰 Cost-Efficient
Polygon L2 = 1700x cheaper than Ethereum
Serverless = Pay only for what you use
Open-source = No vendor lock-in
🛠️ Developer Experience
TypeScript = Type safety, fewer bugs
GraphQL = Efficient data fetching
Comprehensive tests = Ship with confidence
🌐 Future-Proof
Blockchain = Transparent, immutable
NFTs = New revenue streams
API-first = Easy integrations
Technology Timeline
Months 1-3: MVP Development
- Core prediction engine (Rust)
- Web app (Next.js)
- PostgreSQL + Redis setup
- Basic smart contracts (testnet)
- Paper money mode only
Months 4-6: Blockchain Integration
- Smart contract audit
- Polygon mainnet deployment
- Real money predictions enabled
- Payment integrations (Stripe, crypto)
- KYC/AML implementation
Months 7-9: Mobile & NFTs
- React Native apps (iOS + Android)
- NFT badge system live
- First collectible NFT drop
- OpenSea integration
Months 10-12: Scale & Optimize
- Multi-region deployment
- GraphQL API
- Advanced analytics
- Database sharding
- Performance optimization
Year 2: Advanced Features
- AI-powered insights
- Copy-trading functionality
- White-label API
- Cross-chain support (Ethereum, Arbitrum)
Development Team Structure
Core Engineering Team (Year 1)
| Role | Count | Responsibilities | Key Skills |
|---|---|---|---|
| Tech Lead / Architect | 1 | System design, architecture decisions | 10+ years, distributed systems, blockchain |
| Backend Engineers | 3 | Microservices, APIs, databases | Node.js, Rust, PostgreSQL, Redis |
| Frontend Engineers | 2 | Web app, mobile apps | React, Next.js, React Native, TypeScript |
| Blockchain Engineer | 1 | Smart contracts, Web3 integration | Solidity, Ethers.js, Polygon, auditing |
| DevOps Engineer | 1 | Infrastructure, CI/CD, monitoring | AWS, Docker, Kubernetes, Terraform |
| QA Engineer | 1 | Testing, automation, quality assurance | Playwright, k6, security testing |
Total: 9 engineers for Year 1 ($800k budget)