Teamwork in Action: The Journey to AWS Aurora

Over the past 1.5 years, we successfully migrated all our micro-services from MySQL to AWS Aurora. This move has significantly boosted our performance, scalability, and reliability, while also simplifying database management and reducing code complexity.

Team Collaboration

The collaboration between our DBA team and developers was crucial. The DBAs brought their expertise in database architecture, migration strategies, and performance tuning, while the developers ensured application compatibility, optimized queries, and conducted extensive testing. This close teamwork made the transition smooth with minimal disruption.

Key Teamwork Practices

• Regular cross-team syncs for alignment and smooth communication.
• Detailed migration planning with phased rollouts.
• Extensive testing in lower environments before going live.
• Documentation and knowledge sharing to keep everyone on the same page.
• Collaboration & Open Communication – Frequent cross-team syncs, shared documentation, and an open feedback loop ensured everyone stayed aligned. Developers and DBAs worked closely to upskill each other, ensuring a deeper understanding of both database operations and application needs.
• Problem-Solving Mindset – The team embraced challenges as opportunities to improve, always seeking the best long-term solutions.
• Resilience & Adaptability – Over 1.5 years, the team navigated complex migration challenges while staying committed to delivering a smooth transition.
• Celebrating Wins Together – The team recognized every milestone, no matter how small, which kept morale high throughout the project.

Challenges and Solutions

• Minimizing Downtime: Phased rollouts and rigorous testing.
• Schema and Query Compatibility: Query optimization and schema adjustments.
• Performance Tuning: Load testing and fine-tuning configurations.

Highlights

• Implemented a Global Database for seamless disaster recovery in Paris.
• Achieved failover times under 10 seconds.
• Set up a future-ready architecture with Aurora serverless as an option.
• Simplified operations by removing custom automation scripts.
• Reduced the code base and overall system complexity, making future development and maintenance easier.

System Improvements

• Better read and write performance with Aurora’s optimized storage layer.
• Faster failover times ensuring high availability.
• Autoscaling capabilities reducing the need for over-provisioning.
• Improved disaster recovery with global database replication.
• Simplified database management due to Aurora’s managed features, reducing operational overhead.

Team Sentiment

Our team feels a great sense of accomplishment. This was a complex, high-impact migration, and the collaboration, problem-solving, and teamwork made it a rewarding experience. Plus, reducing technical debt by simplifying the system was a big win for everyone.

Key Lessons Learned

• Thorough planning and phased rollouts are crucial for minimizing risks.
• Close collaboration between DBAs and developers ensures a smooth transition.
• Testing at every stage helps catch issues early.
• Automation and simplification reduce long-term operational overhead and make systems more maintainable.

Next Steps

• Evaluate the feasibility of serverless Aurora for cost optimization.
• Continue to fine-tune and monitor performance.
• Leverage Aurora’s advanced features for future scalability.
• Migrate our legacy monolith databases to AWS Aurora.