Migration Plan Template
Purpose
The Migration Plan details the strategy, timeline, and procedures for moving systems, data, or infrastructure from current to target state while minimizing risk and business disruption.
When to Use
- Migrating to cloud infrastructure
- Upgrading major system components
- Consolidating or decomposing systems
- Changing technology platforms
- Data center relocations
- Database migrations
- Infrastructure refactoring
Executive Summary
Provide high-level migration overview:
Migration Overview:
This plan describes the migration of [system/data/infrastructure] from
[current state] to [target state]. The migration uses a [phased/big-bang/
parallel] approach over [timeline] to minimize risk and business disruption.
Key Metrics:
- Total duration: X weeks/months
- Systems affected: [Count]
- Users impacted: [Count]
- Expected downtime: X hours (or zero-downtime)
- Estimated cost: $X
- Risk level: [Low/Medium/High]
- Success criteria: [High-level acceptance criteria]
Section 1: Current State Assessment
Document the existing environment:
Current System Architecture:
[ASCII diagram or description of current state]
System Components:
┌────────────┬──────────────┬──────────────┬────────────┐
│ Component │ Technology │ Version │ Status │
├────────────┼──────────────┼──────────────┼────────────┤
│ Database │ MySQL │ 5.7 │ EOL soon │
│ App Server │ Tomcat │ 8.5 │ Supported │
│ Cache │ Memcached │ 1.4 │ Outdated │
│ Queue │ RabbitMQ │ 3.6 │ EOL │
└────────────┴──────────────┴──────────────┴────────────┘
Current State Challenges:
- MySQL 5.7 reaching end-of-life in October 2025
- RabbitMQ 3.6 lacks features needed for new capabilities
- Memcached performance degrading with dataset growth
- Tomcat 8.5 lacks security updates
- Infrastructure on aging hardware (8+ years old)
Current Performance Metrics:
- Application response time: 500ms P95
- Database query latency: 100ms P95
- Cache hit rate: 60%
- Message queue latency: 50ms P95
- System availability: 99.5%
Data Assets:
- Database size: 500GB
- Daily data growth: 50GB
- Critical customer data: [PII classification]
- Regulatory compliance: GDPR, SOC 2
Current Users & Stakeholders:
- Internal users: 1,000 (Customer Service, Operations)
- External users: 50,000 (Customers)
- API consumers: 20 (Partners)
Section 2: Target State Definition
Define desired end state:
Target Architecture:
[ASCII diagram of target state]
Target System Components:
┌────────────┬──────────────┬──────────────┬────────────┐
│ Component │ Technology │ Version │ Rationale │
├────────────┼──────────────┼──────────────┼────────────┤
│ Database │ PostgreSQL │ 15 │ Modern, │
│ │ │ │ scalable │
│ App Server │ Kubernetes │ 1.28 │ Orchestr. │
│ Cache │ Redis │ 7.2 │ Better │
│ │ │ │ perf │
│ Queue │ Kafka │ 3.6 │ Stream │
│ │ │ │ processing│
└────────────┴──────────────┴──────────────┴────────────┘
Target State Benefits:
- Modern, supported technology stack
- 50% reduction in query latency
- Horizontal scalability
- Event-driven architecture
- Zero-downtime deployments
Target Performance Metrics (Targets):
- Application response time: < 200ms P95
- Database query latency: < 50ms P95
- Cache hit rate: > 85%
- Message queue latency: < 20ms P95
- System availability: 99.99%
Target Data Assets:
- Same database size initially (scalable to 10TB+)
- Data retention policies unchanged
- Enhanced compliance capabilities
- Audit logging improved
Target Environment:
- Deployment: Kubernetes on AWS (EKS)
- Databases: Managed services (RDS PostgreSQL, ElastiCache)
- Monitoring: Prometheus/Grafana, ELK stack
- Infrastructure as Code: Terraform
Section 3: Migration Strategy
Define overall migration approach:
Migration Approach: [Phased/Big-Bang/Parallel/Strangler]
Phased Approach:
- Rationale: Reduces risk by moving systems independently
- Timeline: 12-16 weeks (multiple phases)
- Downtime: Zero (parallel running)
- Complexity: High (system coordination)
- Rollback: Phase-by-phase rollback
┌──────────────┬───────────────────┬────────────┐
│ Phase │ Systems │ Duration │
├──────────────┼───────────────────┼────────────┤
│ Phase 1 │ Infrastructure │ 2 weeks │
│ (Foundation) │ Cache layer │ │
├──────────────┼───────────────────┼────────────┤
│ Phase 2 │ Message queue │ 2 weeks │
│ (Events) │ Event streaming │ │
├──────────────┼───────────────────┼────────────┤
│ Phase 3 │ Database │ 4 weeks │
│ (Data) │ Data migration │ │
│ │ Validation │ │
├──────────────┼───────────────────┼────────────┤
│ Phase 4 │ Application │ 3 weeks │
│ (Compute) │ Deployment │ │
│ │ Cutover │ │
├──────────────┼───────────────────┼────────────┤
│ Phase 5 │ Decommission │ 2 weeks │
│ (Cleanup) │ Old infrastructure│ │
│ │ Optimize costs │ │
└──────────────┴───────────────────┴────────────┘
Alternative: Big-Bang Approach
- Single cutover event (all systems at once)
- Shorter timeline: 4 weeks
- Higher risk (total system dependency)
- Larger outage window (4-6 hours)
- Faster business value realization
- Rejected: Risk too high for critical system
Selected: Phased Approach
- Best balance of risk and timeline
- Allows validation at each phase
- Minimal disruption to users
Section 4: Detailed Wave Planning
PHASE 1: Infrastructure Foundation (Weeks 1-2)
Objectives:
- Set up target infrastructure
- Establish connectivity to current systems
- Validate infrastructure quality
Activities:
Week 1:
- Day 1-2: AWS account setup, VPC configuration
- Day 3-5: Kubernetes cluster setup (EKS)
- Deliverable: EKS cluster running, kubectl access confirmed
Week 2:
- Day 1-3: RDS PostgreSQL setup, backup configured
- Day 4-5: Monitoring/logging setup
- Deliverable: Infrastructure ready for workloads
Success Criteria:
- [ ] EKS cluster operational (3-node minimum)
- [ ] RDS PostgreSQL accessible
- [ ] Monitoring dashboards active
- [ ] Backup/restore tested
- [ ] Network connectivity established
Rollback Plan:
- Rollback: Delete AWS infrastructure (reversible)
- Cost: ~$5k to restart
- Timeline: <1 hour
---
PHASE 2: Event Infrastructure (Weeks 3-4)
Objectives:
- Deploy message queue (Kafka)
- Establish event streaming capability
- Integrate with current system (publishers/subscribers)
Activities:
Week 3:
- Day 1-3: Kafka cluster setup (3 brokers)
- Day 4-5: Topic creation, retention policies
- Deliverable: Kafka cluster operational
Week 4:
- Day 1-3: Event publisher implementation
- Day 4: Consumer implementation
- Day 5: End-to-end testing
- Deliverable: Event streaming validated
Success Criteria:
- [ ] Kafka cluster operational (3+ brokers)
- [ ] Publishers sending events
- [ ] Consumers receiving events
- [ ] Event loss testing (no data loss)
- [ ] Latency target met (<20ms)
Rollback Plan:
- Keep current RabbitMQ active during phase
- Gradual switchover: 10% traffic → Kafka (monitored)
- If issues: Revert to RabbitMQ
- Timeline: <30 minutes
---
PHASE 3: Data Migration (Weeks 5-8)
Objectives:
- Migrate database from MySQL to PostgreSQL
- Validate data integrity
- Establish replication/sync
Activities:
Week 5: Planning & Testing
- Day 1-3: Schema redesign review
- Day 4-5: Data type mapping validation
- Deliverable: Migration plan approved
Week 6: Initial Load
- Day 1-3: Full database dump, initial load to PostgreSQL
- Day 4-5: Data validation, reconciliation
- Deliverable: Initial dataset loaded
Week 7: Replication Setup
- Day 1-3: MySQL → PostgreSQL replication (Debezium + Kafka)
- Day 4-5: Replication lag monitoring
- Deliverable: Replication validated, lag <1 second
Week 8: Cutover Preparation
- Day 1-2: Final validation scripts
- Day 3-4: Cutover rehearsal (non-prod)
- Day 5: Cutover window scheduled, team trained
- Deliverable: Go/no-go decision
Success Criteria:
- [ ] All data migrated accurately
- [ ] Data validation passed (100% match)
- [ ] Replication lag < 1 second
- [ ] Performance targets met
- [ ] Backup/restore tested in PostgreSQL
Rollback Plan:
- Keep MySQL operational until application cutover
- Reverse replication: PostgreSQL → MySQL (if needed)
- Cutover rollback: Switch application back to MySQL
- Timeline: <30 minutes
---
PHASE 4: Application Deployment (Weeks 9-11)
Objectives:
- Deploy application to Kubernetes
- Validate functionality
- Cutover to new infrastructure
Activities:
Week 9: Containerization
- Day 1-3: Application containerization (Docker)
- Day 4-5: Container registry setup, Helm charts
- Deliverable: Application images ready
Week 10: Staging Validation
- Day 1-3: Deploy to staging Kubernetes
- Day 4: Integration testing
- Day 5: Performance testing
- Deliverable: Staging environment validated
Week 11: Production Cutover
- Day 1-2: Canary deployment (10% traffic)
- Day 3: Monitor metrics (error rate, latency)
- Day 4: Increase traffic gradually (25% → 50% → 100%)
- Day 5: Full cutover complete
- Deliverable: Production traffic on new infrastructure
Success Criteria:
- [ ] Application deployed and operational
- [ ] All functionality working (regression tests passing)
- [ ] Performance targets met (response time <200ms P95)
- [ ] Error rate < 0.1%
- [ ] Zero data loss during cutover
Rollback Plan:
- Canary approach allows phased rollback
- If critical issue: Route traffic back to legacy Tomcat
- Database rollback: Switch to MySQL if needed
- Timeline: <15 minutes per phase
---
PHASE 5: Cleanup & Optimization (Weeks 12-13)
Objectives:
- Decommission legacy infrastructure
- Optimize costs
- Prepare for ongoing operations
Activities:
Week 12:
- Day 1-2: Decommission Tomcat servers
- Day 3-4: Decommission MySQL
- Day 5: Cancel old hosting services
- Deliverable: Legacy infrastructure removed
Week 13:
- Day 1-2: Cost optimization review
- Day 3-4: Documentation updates
- Day 5: Lessons learned review
- Deliverable: Optimization complete
Section 5: Testing Strategy
Testing Approach:
Test Phase 1: Infrastructure Validation
- EKS cluster health checks
- Database connectivity tests
- Network latency validation
- Backup/restore verification
Test Phase 2: Data Validation
- Full data consistency checks
- Query result comparison (MySQL vs PostgreSQL)
- Referential integrity validation
- Data type mapping validation
Test Phase 3: Functional Testing
- Regression test suite (100% passing)
- Integration tests between services
- API contract testing
- End-to-end business scenarios
Test Phase 4: Performance Testing
- Load testing (expected peak + 50%)
- Stress testing (until failure point)
- Soak testing (24-hour run)
- Latency percentile testing (P50/P95/P99)
Test Phase 5: Chaos/Resilience Testing
- Component failure scenarios
- Network partition testing
- Database failover testing
- Deployment failure testing
Success Criteria:
- All regression tests passing (100%)
- Performance targets met
- Zero unplanned downtime
- Error rate < 0.01%
Section 6: Risk Assessment
Risk Matrix:
┌──────────────────────┬────────────┬────────────┬──────────────────┐
│ Risk │ Likelihood │ Impact │ Mitigation │
├──────────────────────┼────────────┼────────────┼──────────────────┤
│ Data loss during │ Medium │ Critical │ Multiple backups │
│ migration │ │ │ Validation checks│
├──────────────────────┼────────────┼────────────┼──────────────────┤
│ Performance worse │ Medium │ High │ Load testing │
│ than current │ │ │ Tuning before │
├──────────────────────┼────────────┼────────────┼──────────────────┤
│ Application │ Low │ High │ Thorough testing │
│ compatibility │ │ │ Staging validate │
├──────────────────────┼────────────┼────────────┼──────────────────┤
│ Vendor issues │ Low │ High │ AWS support plan │
│ (AWS/Kubernetes) │ │ │ on-call response │
├──────────────────────┼────────────┼────────────┼──────────────────┤
│ Team capability │ Medium │ Medium │ Training plan │
│ gaps │ │ │ Vendor training │
├──────────────────────┼────────────┼────────────┼──────────────────┤
│ Cost overruns │ Medium │ Medium │ Budget tracking │
│ │ │ │ Reserve (20%) │
└──────────────────────┴────────────┴────────────┴──────────────────┘
Risk Escalation Process:
- Severity P0 (Critical): Notify CTO immediately, escalation path
- Severity P1 (High): Notify project sponsor, daily updates
- Severity P2 (Medium): Notify project lead, weekly updates
- Severity P3 (Low): Track in project log, monthly updates
Section 7: Success Criteria & Go-Live Decision
Pre-Cutover Validation Checklist:
☐ All regression tests passing (100%)
☐ Performance targets validated in staging
☐ Data integrity verified
☐ Replication lag < 1 second
☐ Monitoring/alerting operational
☐ Runbooks completed
☐ On-call team trained and ready
☐ Communication plan activated
☐ Executive sponsor sign-off obtained
Go-Live Criteria:
☐ All validation criteria met above
☐ Rollback plan tested and ready
☐ Support team on standby
☐ Incident response team ready
Production Targets (Post-Cutover):
- Application availability: > 99.9%
- Error rate: < 0.1%
- Response time P95: < 200ms
- Database latency P95: < 50ms
- Cache hit rate: > 80%
Post-Cutover Validation (Week 1):
- Daily metrics review
- Customer feedback monitoring
- Error rate tracking
- Performance stability assessment
- Cost validation
Go/No-Go Decision:
After Week 1 of production operation:
☐ GO: Migration successful, proceed with cleanup
☐ CONTINUE MONITORING: Address minor issues, recheck Week 2
☐ ROLLBACK: Critical issues found, execute rollback plan
Section 8: Communication Plan
Stakeholder Communication:
Pre-Migration (4 weeks prior):
- Executive leadership: Project overview, timeline, risks
- Operations team: Detailed technical training
- Support team: Runbook review, incident response
- Customers: Notification of maintenance window (if applicable)
Week Before Cutover:
- All teams: Final review meeting
- Operations: Deployment procedure walkthrough
- Support: Incident scenarios and response procedures
During Cutover (Cutover Weekend):
- Updates every 15 minutes to all stakeholders
- Issues log: Track all problems and resolutions
- Executive sponsor: Real-time updates on critical issues
Post-Cutover:
- Daily updates for Week 1 (if any issues)
- Weekly updates for Month 1
- Lessons learned review (Week 2)
Communication Channels:
- Slack: Real-time updates
- Email: Formal status updates
- War room: Central decision point (cutover day)
Section 9: Migration Checklist
Pre-Migration:
☐ Infrastructure designed and reviewed
☐ Migration plan documented
☐ Risk assessment complete
☐ Testing plan defined
☐ Rollback procedures documented
☐ Team trained (technical and operational)
☐ Monitoring/alerting configured
☐ Backup strategy tested
☐ Executive approvals obtained
☐ Communication plan prepared
☐ Support team briefed
☐ Customer communication sent (if applicable)
Migration Week:
☐ Infrastructure provisioned
☐ Configuration validated
☐ Data migration executed
☐ Data validation passed
☐ Replication active and monitoring
☐ Application deployed to staging
☐ Staging validation complete
☐ Application ready for production
Cutover Day:
☐ Monitoring dashboard active
☐ On-call team ready
☐ Support team on standby
☐ Incident response team ready
☐ Executive sponsor available
☐ Communication channels active
☐ Rollback plan at ready status
Post-Cutover:
☐ Production validation metrics green
☐ Customer issues tracked and resolved
☐ Runbooks updated with real issues
☐ Performance tuning completed
☐ Cost analysis completed
☐ Lessons learned documented
☐ Legacy infrastructure decommissioned
☐ Team retrospective conducted
Section 10: Timeline & Dependencies
Gantt Chart Overview:
Week 1-2: [▓▓▓▓▓] Infrastructure Foundation
Week 3-4: [ ▓▓▓▓▓] Event Infrastructure
Week 5-8: [ ▓▓▓▓▓▓▓▓] Data Migration
Week 9-11: [ ▓▓▓▓▓▓▓] Application Deployment
Week 12-13: [ ▓▓▓▓] Cleanup & Optimization
Critical Path:
Infrastructure → Data Migration → Application Deployment → Cutover
Dependencies:
- Infrastructure must complete before data migration
- Data must be migrated before application deployment
- Application tested in staging before production cutover
- Legacy systems must remain operational until cutover complete
Milestones:
- Week 2: Infrastructure complete & validated
- Week 4: Event infrastructure complete & tested
- Week 8: Data migration complete & validated
- Week 11: Application cutover complete
- Week 13: Legacy systems decommissioned
Key Decision Points:
- End of Week 2: Go/No-Go on infrastructure
- End of Week 8: Go/No-Go on data migration
- End of Week 10: Go/No-Go on application readiness
- Week 11: Final go-live decision
Related Resources
Status: Complete
Last Updated: November 2025
Version: 1.0
Contributors: Architecture Practice Team