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Database Migration

Zero-Downtime Database Migration: PostgreSQL to Aurora

Designed and implemented a production-ready framework for migrating a 500GB PostgreSQL database to Aurora PostgreSQL with zero downtime using AWS DMS, Terraform, and automated validation.

SaaS PlatformTechnology / SaaS
9 min read
12/3/2024
Key Results
Application Downtime
0 seconds
Zero downtime achieved
Data Migrated
512 GB
Full load in 3h 22m
Read Latency (p95)
27ms
40% reduction (from 45ms)

Designed and implemented a production-ready framework for migrating a 500GB PostgreSQL database to Aurora PostgreSQL with zero downtime using AWS DMS, Terraform, and automated validation.

0 seconds
Application Downtime
Zero downtime achieved
512 GB
Data Migrated
Full load in 3h 22m
27ms
Read Latency (p95)
40% reduction (from 45ms)

The Challenge

The client operated a self-managed PostgreSQL database serving 50,000 daily active users. The team needed to migrate to Aurora PostgreSQL for managed operations and better scalability, but could not accept any downtime during the transition.

500GB production database with continuous write operations
Zero maintenance window available for migration
Manual backup and replication processes consuming engineering time
Limited disaster recovery capabilities with 24-hour RPO
Strict data integrity requirements for financial transaction data
Need for reproducible migration process across environments

Our Approach

Implemented a blue-green database migration strategy using AWS Database Migration Service with automated validation, cutover orchestration, and rollback capabilities. The solution was built entirely with Infrastructure as Code for reproducibility.

AWS DMSAurora PostgreSQLTerraformPythonGitHub ActionsCloudWatch

Implementation Timeline

Total Duration: 4 weeks development, 12 minutes production cutover

1

Infrastructure Foundation

1 week

  • Modular Terraform for DMS, Aurora, networking, monitoring
  • Multi-AZ replication instance configuration
  • Security group and network rules setup
  • CloudWatch dashboards and alerting
2

Validation Framework

1 week

  • Row count comparison between source and target
  • MD5 checksum verification of sample data
  • Sequence value synchronization checks
  • DMS health and replication lag monitoring
3

Cutover Orchestration

1 week

  • Multi-phase cutover script with state persistence
  • Automatic rollback capability at each phase
  • Connection draining and final sync procedures
  • Post-cutover validation checks
4

CI/CD Integration

1 week

  • GitHub Actions workflows for all operations
  • Manual approval gates for production cutover
  • Secrets management via AWS Secrets Manager
  • Artifact preservation for audit trail

Technical Architecture

Blue-green database migration architecture with continuous replication, automated validation, and orchestrated cutover for zero-downtime transitions.

AWS DMS for full load and CDC replication
Aurora PostgreSQL with read replicas
Terraform modules for reproducible infrastructure
Python automation for validation and cutover
GitHub Actions for CI/CD workflows
CloudWatch for monitoring and alerting

Results & Impact

0 seconds
Application Downtime
Zero downtime achieved
512 GB
Data Migrated
Full load in 3h 22m
27ms
Read Latency (p95)
40% reduction (from 45ms)
0 hours
Monthly Maintenance
100% reduction (from 12 hours)
5 minutes
Recovery Point Objective
288x improvement (from 24 hours)
2.1 seconds
CDC Lag at Cutover
Near real-time sync

Business Benefits

Zero downtime migration with full data integrity verification
Reproducible framework used for subsequent environment migrations
Eliminated database maintenance overhead for engineering team
Point-in-time recovery now available within 5 minutes
Complete audit trail of validation results and cutover states
40% improvement in read latency from Aurora optimizations
The migration was completely transparent to our users. We went from constantly worrying about the database to not thinking about it at all. The tooling delivered has become part of our standard infrastructure operations.
Engineering Lead
Platform Team

Key Learnings

Test validation scripts as thoroughly as the migration itself
Size DMS instances appropriately to avoid CPU bottlenecks during full load
Monitor CDC lag obsessively and set alarms for threshold breaches
Keep source database running for 48 hours post-cutover as safety net
Communicate status updates frequently during migration day

Recommendations

Run through the complete process in staging before production
Document the runbook and rehearse cutover procedures
Set up CloudWatch alarms for replication lag before migration
Plan for unexpected dependencies in data migration
Database MigrationAWS DMSPostgreSQLAuroraTerraformZero Downtime

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