Case Study - Legacy to Cloud: 5TB Migration for a Betting Platform with Luce
A data migration solution for a high-volume betting platform, moving 5TB of operational data from legacy MySQL systems to cloud-native architecture with minimal downtime.
- Client
- Betting Platform
- Year
- Service
- Data Migration, Cloud Architecture, Legacy Modernization
Executive Summary
In February 2026, We executed a critical data migration for a high-volume betting platform, moving 5TB of operational data from legacy MySQL systems to a cloud-native architecture. The project achieved zero data loss, production-grade uptime during migration, and 50% performance improvement while establishing a scalable foundation for future growth.
The Challenge: MySQL Bottlenecks in Operational Systems
The betting platform faced critical performance and scalability challenges:
System Bottlenecks
- Database Performance: MySQL struggling with 10M+ daily transactions
- Query Latency: 5-10 second response times during peak hours
- Storage Limitations: 5TB data approaching hardware capacity limits
- Backup Issues: 8+ hour backup windows causing operational constraints
- Scaling Problems: Vertical scaling no longer cost-effective
Business Impact
- User Experience: Slow response times affecting betting experience
- Revenue Loss: System downtime during peak betting hours
- Operational Costs: Expensive hardware maintenance and upgrades
- Competitive Disadvantage: Unable to support new features and markets
- Risk Management: Single points of failure in critical systems
Technical Constraints
- Legacy Architecture: Monolithic MySQL setup with limited flexibility
- Data Volume: 5TB of historical and real-time betting data
- Zero-Downtime Requirement: Critical for 24/7 betting operations
- Data Consistency: Complex relationships across betting, user, and financial data
- Compliance Requirements: Gaming regulations and audit trails
Solution: Migration Strategy
We implemented a migration strategy using modern data stack technologies:
Technical Stack
- Debezium: Change Data Capture (CDC) for real-time replication
- Airbyte: Data ingestion and transformation pipeline
- DBT: Data modeling and transformation layer
- BigQuery: Cloud data warehouse for analytics
- Cloud SQL: Managed MySQL for operational data
- Terraform: Infrastructure as Code for deployment
Migration Architecture
Our migration strategy followed a phased approach with real-time replication and minimal downtime, ensuring continuous operations throughout the migration process.
Legacy to Cloud Migration Architecture
Legacy Phase
- • MySQL bottlenecks
- • 5-10s response times
- • 5TB data volume
- • Hardware limitations
Migration Phase
- • Debezium CDC
- • Airbyte ingestion
- • DBT transformations
- • Real-time replication
Cloud Phase
- • Cloud SQL operational
- • BigQuery analytics
- • 25% cost savings
- • Scalable architecture
Technical Implementation
1. Change Data Capture with Debezium
Implemented real-time data replication from MySQL to cloud systems:
The full configuration reference is available on request.
2. Data Pipeline with Airbyte
Built robust data ingestion pipeline:
The full configuration reference is available on request.
3. Data Transformation with DBT
Implemented data modeling:
The full data warehouse query reference is available on request.
4. Migration Strategy and Timeline
Implemented a phased migration approach:
The full data warehouse query reference is available on request.
Measurable Results
- Data Migrated
- 5TB
- Downtime
- 3 min
- Cost Savings
- —
- Daily Transactions
- 10M+
- Uptime availability
- High
- Query Response
- < 1s
- Operations
- 24/7
- Data Loss
- 0
Performance Improvements
Before Migration
- Query Response: 5-10 seconds during peak hours
- Backup Time: 8+ hours
- Scaling: Manual vertical scaling required
- Uptime: 99.5% with frequent maintenance windows
- Cost: High hardware and maintenance costs
After Migration
- Query Response: < 1 second consistently
- Backup Time: 15 minutes with automated snapshots
- Scaling: Automatic horizontal scaling
- Uptime: 99.9% with zero-downtime deployments
- Cost: meaningful reduction in total infrastructure costs
Migration Benefits
Operational Improvements
- Real-time Processing: Sub-second data replication across systems
- Automated Scaling: Dynamic resource allocation based on demand
- Disaster Recovery: Multi-region backup and failover capabilities
- Monitoring: observability and alerting
- Compliance: Enhanced audit trails and data governance
Business Impact
- User Experience: Faster betting interface and real-time updates
- Revenue Growth: Support for higher transaction volumes
- Market Expansion: Ability to enter new markets and jurisdictions
- Feature Development: Faster deployment of new betting features
- Risk Management: Improved fraud detection and compliance monitoring
Migration Template
Our implementation provides a migration template that includes:
- CDC Configuration
- Data Pipeline Setup
- Validation Procedures
- Rollback Strategies
- Performance Testing
- Monitoring Setup
- Documentation
- Training Materials
Call to Action
Ready to modernize your legacy data infrastructure? Clone our migration template and start your journey:
Conclusion
The legacy to cloud migration demonstrates that large-scale data migration can be achieved with minimal disruption while delivering significant performance improvements. By leveraging modern migration technologies and a well-planned migration strategy, Luce achieved:
- Zero Data Loss: Complete data integrity throughout migration
- Minimal Downtime: production-grade uptime during critical migration period
- Performance Improvement: materially faster query performance
- Scalability: Cloud-native architecture supporting future growth
- Operational Continuity: Seamless transition with no business disruption
This project serves as a blueprint for other organizations seeking to modernize legacy data infrastructure while maintaining operational continuity. The migration template provides a proven framework for achieving similar results across different industries and data volumes.