Migrating a High-Traffic MySQL Database to AWS Aurora

Abstract geometric gradient illustration

This article is a historical account from the original blog. Technical and commercial conditions may have changed.

A staged database migration

The Problem: Outgrowing On-Premise Infrastructure

Our legacy MySQL environment had served us well, but we were hitting clear limitations:

Choosing the Right Tools for the Job

Initially, we considered using AWS Database Migration Service (DMS), but after internal testing, we decided it wasn’t the right fit for our use case. We wanted more control and transparency.

Instead, we built a custom pipeline using:

This gave us the control we needed to fine-tune every step of the process.

☁️ Setting Up Aurora: Scalable, Reliable, and Cost-Efficient

Running in Parallel: 2 Months of Testing and Validation

During this period:

This approach gave us the confidence to proceed with the switch without surprises.

Simplifying the Architecture with ProxySQL

With ProxySQL, we were able to:

This abstraction layer gave us a safe buffer and made integration far easier.

The Final Cutover: Smooth, Fast, and Nearly Invisible

Results That Matter

Final Thoughts from DasMeta

Thinking About Your Own Migration?

Migrating a High-Traffic MySQL Database to AWS Aurora

This article is a historical account from the original blog. Technical and commercial conditions may have changed.

A staged database migration

The Problem: Outgrowing On-Premise Infrastructure

Our legacy MySQL environment had served us well, but we were hitting clear limitations:

Choosing the Right Tools for the Job

Initially, we considered using AWS Database Migration Service (DMS), but after internal testing, we decided it wasn’t the right fit for our use case. We wanted more control and transparency.

Instead, we built a custom pipeline using:

This gave us the control we needed to fine-tune every step of the process.

☁️ Setting Up Aurora: Scalable, Reliable, and Cost-Efficient

Running in Parallel: 2 Months of Testing and Validation

During this period:

This approach gave us the confidence to proceed with the switch without surprises.

Simplifying the Architecture with ProxySQL

With ProxySQL, we were able to:

This abstraction layer gave us a safe buffer and made integration far easier.

The Final Cutover: Smooth, Fast, and Nearly Invisible

Results That Matter

Final Thoughts from DasMeta

Thinking About Your Own Migration?

Key takeaways

Assess workload dependencies and plan the migration in stages.
Validate application behavior and data before cutover.
Test monitoring, recovery and rollback against the actual environment.

FAQ

Why run the source and target databases in parallel?

Parallel operation can provide time to validate data, application behavior and performance before cutover.

Is AWS DMS required for every migration?

No. The migration approach depends on the workload, compatibility, operating requirements and testing.

What should teams test before a database cutover?

Test data consistency, application behavior, performance, recovery and the cutover and rollback procedures.

Migrating a High-Traffic MySQL Database to AWS Aurora