cloudthinker-ai Database Cloud Migration Plan
Phase 1: Database Assessment
- Profile the source database
- Database engine and version
- Schema count, table count, total data size
- Stored procedures, triggers, and functions inventory
- Extensions and plugins in use
- Connection patterns and peak concurrent connections
- Identify compatibility issues with target service
- Document RPO (Recovery Point Objective) and RTO (Recovery Time Objective)
- Baseline current performance metrics
Compatibility Checklist
| Feature | Source DB | Target DB | Compatible | Action Needed |
|---|---|---|---|---|
| Data types | [ ] | |||
| Stored procedures | [ ] | |||
| Triggers | [ ] | |||
| Extensions | [ ] | |||
| Character encoding | [ ] | |||
| Collation | [ ] |
Phase 2: Migration Method Selection
Decision Matrix
| Method | Downtime | Complexity | Data Loss Risk | Best For |
|---|---|---|---|---|
| Dump & Restore | High | Low | Low | Small DBs (<50GB) |
| Continuous Replication | Low | High | Very Low | Large production DBs |
| Cloud Migration Service | Medium | Medium | Low | Supported engines |
| Application-level | Variable | Medium | Medium | Schema changes needed |
- Select migration method based on requirements
- Plan schema conversion if changing engines
- Design replication topology for continuous sync
- Plan cutover window and communication
Phase 3: Pre-Migration Setup
- Provision target cloud database instance
- Configure networking (VPC peering, private endpoints)
- Set up replication user and permissions on source
- Test connectivity between source and target
- Run schema migration or conversion scripts
Phase 4: Data Migration
- Execute initial full data load
- Set up continuous replication (if applicable)
- Monitor replication lag and error rates
- Validate row counts and checksums
- Test application connectivity to target database
Phase 5: Cutover
- Stop application writes to source database
- Wait for replication to catch up (lag = 0)
- Verify data consistency with checksums
- Update application connection strings
- Start application against target database
- Monitor error rates and performance
Phase 6: Post-Migration Validation
- Run data integrity checks (row counts, checksums, spot checks)
- Execute application test suite against new database
- Compare query performance against baseline
- Validate backup and recovery procedures
- Keep source database available for rollback period
Counter-Rationalizations
| Shortcut | Counter | Why |
|---|---|---|
| "We can skip some steps for this case" | Adapt the workflow steps, don't skip them | Skipped steps are where incidents and oversights originate |
| "The user seems to already know what to do" | Complete all workflow phases with the user | The workflow catches blind spots that experience alone misses |
| "This is a minor case, full process is overkill" | Scale the process down, don't turn it off | Minor cases become major when unstructured; the process scales, not disappears |
| "I'll fill in the details later" | Complete each section before moving on | Deferred details are forgotten; real-time capture is more accurate |
| "The template output isn't necessary" | Always produce the structured output format | Structured output enables comparison, audit trails, and handoff to other teams |
Output Format
- Assessment Report: Source DB profile and compatibility analysis
- Migration Runbook: Step-by-step procedures with rollback at each phase
- Data Validation Report: Integrity checks and comparison results
- Performance Comparison: Query latency before and after migration
- Cutover Communication: Timeline and stakeholder notifications
Action Items
- Complete source database profiling
- Resolve compatibility issues identified in assessment
- Provision and configure target database
- Execute and validate test migration in staging
- Schedule production cutover window
- Monitor target database for 7 days post-migration
- Decommission source database after stabilization