Migrating SQL Server Workloads to Amazon RDS for Scalability and Cost Optimization

The client is a mid-sized enterprise software provider that relies heavily on Microsoft SQL Server databases to power its core applications. With a growing customer base and expanding data volumes, the company’s on-premises SQL Server infrastructure was under increasing strain. The client’s small IT team was spending a significant portion of its time managing database servers, which distracted from developing new features and improving the product. The company engaged our cloud migration team to modernize its database platform. The goal was to improve scalability and performance while controlling costs, allowing the client’s engineers to focus on core business value rather than routine infrastructure maintenance.

50%

cost savings

99.95%

uptime, ensuring continuous availability

30%

faster queries, improving user experience

About
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Problem Statement

The on-premises SQL Server is nearing 90% capacity, creating an urgent scalability issue.
Hardware upgrades and license renewals are costly (25% increase) and slow, delaying growth by 4–6 weeks.
Peak usage causes a 30% drop in system performance and results in 8–10 hours of downtime monthly.
The IT team is overburdened, spending 60% of their time on maintenance instead of driving innovation.

Industry: Enterprise Software & Cloud Solutions
Services: SQL Server Cloud Migration
Location: United States

Solution Approach

Assessed 1.2 TB SQL Server workload, targeting 30% lower latency and 99.9% availability.
Set up Amazon RDS (Multi-AZ), IAM roles, and CloudWatch for secure, high-availability cloud operations.
Migrated data using AWS DMS with under 6-hour load time and real-time sync (CDC) under 5-second lag.
Executed cutover with only 3 minutes of downtime and optimized performance for 25% faster queries.
Decommissioned on-prem servers, trained IT staff, and implemented proactive monitoring to cut incident response time by 50%.

Benefits

Improved scalability and performance with up to 30% faster queries and seamless on-demand resource scaling.
Achieved ~50% cost savings using pay-as-you-go pricing and optimized resource usage.
Ensured 99.95% availability with Multi-AZ setup and automated failover under 5 minutes.
Reduced operational overhead by automating maintenance and simplifying management with Amazon RDS.

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