Abstract

Migrating legacy databases to cloud-based platforms is an essential transformation step for businesses seeking elasticity, dependability, and financial efficiency. This work provides an impact-focused assessment of migrating multiple legacy systems to AWS RDS with PostgreSQL. Through real-world schema and workload simulation, some aspects of the migration were evaluated concerning key performance indicators and compatibility benchmarks. The heterogeneous schema conversion achieved an average accuracy rate of 92.4%. Latency on post-migration queries dropped an average of 47% compared to legacy system post-migration latency. Supplied peak-load benchmarks produced an average of 38% CPU savings and as much as 60% improvement in IOPS from RDS instances with auto-scaling while DMS issued downtime events capped at 3 minutes in 84% of cases. These outcomes prove that the cloud-based architecture configuration does surpass classic design not merely in throughput but in system availability as well as operational cost efficiency. Erroneous observations coupled with infrequent rest points and SLA trends informed the formulated practical best practices.