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How to Manage Database Migration Projects
Database migrations are high-risk projects requiring careful coordination between teams and meticulous tracking of dependencies. GitScrum's milestone tracking, checklist features, and cross-team visibility help organizations plan migrations systematically, track progress against critical checkpoints, and maintain clear communication throughout the process.
Migration Project Phases
| Phase | Activities | Duration |
|---|---|---|
| Assessment | Schema analysis, size estimation, risk identification | 1-2 weeks |
| Planning | Migration strategy, testing plan, rollback procedures | 1-2 weeks |
| Development | Scripts, tools, application updates | 2-4 weeks |
| Testing | Data validation, performance testing, DR testing | 2-4 weeks |
| Migration | Execute migration, validation, cutover | 1-3 days |
| Post-Migration | Monitoring, cleanup, documentation | 1 week |
Migration Project Structure
DATABASE MIGRATION EPIC STRUCTURE
Epic: Migrate from MySQL to PostgreSQL
├── Phase 1: Assessment
│ ├── Schema inventory and analysis
│ ├── Data volume assessment
│ ├── Application dependency mapping
│ ├── Risk identification
│ └── Stakeholder communication plan
│
├── Phase 2: Planning
│ ├── Choose migration strategy
│ ├── Design schema mapping
│ ├── Create test data sets
│ ├── Define validation criteria
│ └── Create rollback procedures
│
├── Phase 3: Development
│ ├── Schema migration scripts
│ ├── Data transformation scripts
│ ├── Application dual-write support
│ ├── Feature flags for database
│ └── Monitoring and alerting
│
├── Phase 4: Testing
│ ├── Migrate staging environment
│ ├── Data validation tests
│ ├── Performance benchmarking
│ ├── Application integration tests
│ └── Disaster recovery test
│
├── Phase 5: Migration Execution
│ ├── Final production backup
│ ├── Execute migration
│ ├── Data validation
│ ├── Application cutover
│ └── Performance verification
│
└── Phase 6: Post-Migration
├── Extended monitoring
├── Old database decommission
├── Documentation update
└── Lessons learned
Migration Strategy Options
STRATEGY SELECTION
1. BIG BANG MIGRATION
┌─────────────────────────────────────────────────┐
│ Schedule downtime │
│ Migrate all data at once │
│ Cut over application │
│ │
│ Pros: Simpler, single point of change │
│ Cons: Downtime required, high risk │
│ Best for: Small datasets, acceptable downtime │
└─────────────────────────────────────────────────┘
2. DUAL-WRITE MIGRATION
┌─────────────────────────────────────────────────┐
│ Write to both databases simultaneously │
│ Migrate historical data in background │
│ Gradually shift reads to new database │
│ Disable writes to old database │
│ │
│ Pros: Zero downtime, gradual rollout │
│ Cons: Complex implementation, consistency │
│ Best for: High-availability requirements │
└─────────────────────────────────────────────────┘
3. FEATURE FLAG MIGRATION
┌─────────────────────────────────────────────────┐
│ New features use new database │
│ Old features continue on old database │
│ Gradually migrate features │
│ Decommission old database when empty │
│ │
│ Pros: Low risk, parallel operation │
│ Cons: Longer timeline, complexity │
│ Best for: Large migrations, risk-averse │
└─────────────────────────────────────────────────┘
Validation Checklist
DATA VALIDATION CHECKLIST
PRE-MIGRATION:
□ Row counts match between source and target
□ Schema mapping verified
□ All data types correctly converted
□ Foreign key relationships preserved
□ Indexes created and optimized
POST-MIGRATION:
□ Sample record comparison (1% or 1000 records)
□ Aggregate validation (sums, counts)
□ Edge cases verified (nulls, special chars)
□ Date/time conversions correct
□ Application queries return expected results
PERFORMANCE:
□ Query performance meets baseline
□ Write performance acceptable
□ Index usage verified
□ Connection pooling configured
□ No unexpected locks or blocking
APPLICATION:
□ All CRUD operations working
□ Transactions behaving correctly
□ Error handling for new error types
□ Logging shows correct database calls
□ Monitoring shows healthy metrics
Risk Mitigation
MIGRATION RISK MATRIX
Risk Mitigation
─────────────────────────────────────────────────
Data loss Backups before each step
Validation at each stage
Dry run on staging
Performance regression Benchmark before/after
Index optimization
Query analysis
Application failures Dual-write testing
Feature flags
Rollback procedures
Extended downtime Time-box migrations
Practice runs
Rollback triggers
Missed data Full schema inventory
Dependency tracking
Validation scripts
Best Practices
- Practice migration multiple times on staging
- Validate data at every step
- Have clear rollback triggers and procedures
- Communicate broadly about timeline and risks
- Monitor aggressively during and after migration
- Keep old database available for 1-2 weeks
- Document decisions and deviations
- Run post-mortem even if successful
Anti-Patterns
✗ Big bang migration without practice
✗ No rollback plan
✗ Skipping validation steps
✗ Single person owns entire migration
✗ Migrating during peak traffic
✗ Decommissioning old DB immediately