Multi-Cloud Migrations

Overview

Led multiple cloud migration initiatives including AWS to Azure migrations, database platform changes, and infrastructure modernization projects with zero-downtime cutover requirements.

Problem

Organizations frequently need to migrate between cloud providers due to:

• Cost optimization opportunities
• Compliance and data residency requirements
• Consolidation with existing enterprise agreements
• Performance improvements for specific workloads

The challenge is executing these migrations without disrupting production services.

What I Built

Migration Framework

A reusable framework for planning and executing cloud migrations:

Case Study: AWS to Azure Migration

Context: Full infrastructure migration for a B2B SaaS platform

Before:

After:

Migration Timeline:

Data Migration Strategy

Database Migration (RDS to Cosmos DB PostgreSQL):

Object Storage Migration (S3 to Blob):

1. AzCopy for bulk transfer
2. Dual-write during transition
3. Lazy migration for historical data
4. Verification via checksums

Reliability & Operations

Cutover Checklist

Pre-cutover validation:

• All services deployed and healthy
• Data replication lag < 1 minute
• DNS TTL reduced to 60 seconds
• Rollback scripts tested
• War room scheduled
• Customer communication sent

During cutover:

• Enable maintenance page
• Stop writes to old system
• Final data sync
• Update DNS/traffic manager
• Validate core flows
• Enable writes on new system
• Monitor error rates

Post-cutover:

• All services green
• Error rate < baseline + 1%
• Latency within acceptable range
• Data integrity verified
• Customer spot checks passed

Rollback Procedure

IF error_rate > 5% OR latency > 2x baseline:
  1. Revert DNS to old system (instant)
  2. Stop writes on new system
  3. Assess data delta
  4. Sync any data written to new system back to old
  5. Resume normal operation on old system
  6. Post-mortem and retry planning

Monitoring During Migration

Key Metrics:

• Request latency (p50, p95, p99)
• Error rate by endpoint
• Database connection pool utilization
• Queue depth and processing rate
• Memory and CPU utilization

Alerts (Tightened):

• Error rate > 1% (normally 2%)
• p95 latency > 500ms (normally 1s)
• Any 5xx errors from new infrastructure

Tech Stack

• Infrastructure as Code: Terraform (multi-cloud)
• Data Migration: Azure DMS, AzCopy, custom scripts
• Orchestration: GitHub Actions, custom runbooks
• Monitoring: Datadog (cross-cloud visibility)
• Traffic Management: Azure Traffic Manager, AWS Route53

What I Owned

• Migration strategy and architecture
• Risk assessment and mitigation planning
• Runbook creation and team training
• Cutover execution and coordination
• Post-migration optimization

Results

• Zero-downtime cutover (30-second write pause)
• 25% cost reduction post-migration
• Improved latency for APAC users
• Successfully migrated 2TB of data
• All customer SLAs maintained

Lessons Learned

1. Over-communicate: Stakeholders should never be surprised
2. Test everything: Especially rollback procedures
3. Monitor aggressively: Tighter thresholds during migration
4. Keep old system longer: You'll be glad you did
5. Document decisions: Future you will thank present you

Links

• Migration runbook template: Available on request
• Cost analysis spreadsheet: Available on request