database-cloud-migration

name	database-cloud-migration
enabled	true
description	Use when performing database cloud migration — guides the migration of databases to cloud-managed services, covering schema compatibility analysis, data transfer methods, replication setup, cutover procedures, and post-migration validation. Supports relational, NoSQL, and data warehouse migrations with minimal data loss risk.
required_connections	[{"prefix":"database","label":"Source Database"},{"prefix":"cloud-db","label":"Target Cloud Database Service"}]
config_fields	[{"key":"source_db_engine","label":"Source Database Engine","required":true,"placeholder":"e.g., PostgreSQL 14, Oracle 19c, MongoDB 6"},{"key":"target_db_service","label":"Target Cloud Database Service","required":true,"placeholder":"e.g., Amazon RDS, Cloud SQL, Azure SQL"},{"key":"data_volume_gb","label":"Approximate Data Volume (GB)","required":true,"placeholder":"e.g., 500"}]
features	["CLOUD_MIGRATION","DATABASE"]

Database Cloud Migration Plan

Phase 1: Database Assessment

1. 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
2. Identify compatibility issues with target service
3. Document RPO (Recovery Point Objective) and RTO (Recovery Time Objective)
4. 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

1. Select migration method based on requirements
2. Plan schema conversion if changing engines
3. Design replication topology for continuous sync
4. Plan cutover window and communication

Phase 3: Pre-Migration Setup

1. Provision target cloud database instance
2. Configure networking (VPC peering, private endpoints)
3. Set up replication user and permissions on source
4. Test connectivity between source and target
5. Run schema migration or conversion scripts

Phase 4: Data Migration

1. Execute initial full data load
2. Set up continuous replication (if applicable)
3. Monitor replication lag and error rates
4. Validate row counts and checksums
5. Test application connectivity to target database

Phase 5: Cutover

1. Stop application writes to source database
2. Wait for replication to catch up (lag = 0)
3. Verify data consistency with checksums
4. Update application connection strings
5. Start application against target database
6. Monitor error rates and performance

Phase 6: Post-Migration Validation

1. Run data integrity checks (row counts, checksums, spot checks)
2. Execute application test suite against new database
3. Compare query performance against baseline
4. Validate backup and recovery procedures
5. 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