Tuned Global cuts music platform onboarding from 2 weeks to 2 days

To support rising ingestion volumes and maintain sub-200 millisecond API response times for its enterprise customers, Tuned Global modernized its database on Amazon Web Services (AWS). The B2B music streaming infrastructure provider migrated from Microsoft SQL Server to Amazon Aurora PostgreSQL and modernized its extract, transform, and load (ETL) architecture to improve throughput and scalability. As a result, Tuned Global increased ingestion capacity from 2 million to 20 million tracks per day, reduced customer onboarding timelines by about 90 percent from up to 2 weeks to 1–2 days, achieved 3–5 times faster query performance, and lowered infrastructure costs by 33 percent.

As Tuned Global’s customer base and content volumes continued to grow, its B2B music streaming cloud platform experienced increasing pressure from both catalog ingestion and stream consumption workloads. New customers often brought catalogs of 30–60 million tracks that needed to be ingested, standardized, enriched, and made available through more than 500 APIs. Yahya Bilal, CTO, Tuned Global, says, “Although we could scale our compute layer during large onboarding events, all write activity was concentrated through a single Microsoft SQL Server database, which required careful workload management during large ingestion events.”

At the same time, customer-facing APIs were expected to deliver sub-200 millisecond response times. During peak periods, latency could increase from around 200 milliseconds to 600–800 milliseconds, highlighting the need for a more elastic architecture to maintain consistent delivery at scale. The ETL processes that moved data from the master database to customer-facing stores were linear and SQL-based, limiting throughput and extending onboarding timelines to as long as two weeks for large catalogs.

The SQL Server environment also required manual monitoring and pre-scaling to manage traffic spikes, resulting in operational overhead and underutilized compute during off-peak periods. To eliminate database contention, reduce onboarding delays, and remove manual scaling from critical workflows, Tuned Global needed to modernize its core database layer.

To eliminate database constraints, Tuned Global worked with AWS Partner SourceFuse to assess its Microsoft SQL Server environment and migrate both its master catalog ingestion database and customer-facing store database to Amazon Aurora PostgreSQL. Rather than modernizing only one layer, the company chose to replatform both simultaneously to prevent recurring bottlenecks and to establish a consistent architecture across music ingestion and stream consumption workloads.

Amazon Aurora PostgreSQL was selected for its ability to independently scale reader and writer instances—an essential capability for handling write-heavy ingestion workloads and read-heavy API consumption patterns that occur at different times of day. Amazon Aurora Serverless also enabled on-demand scaling, removing the need for manual pre-scaling and near real-time database monitoring during traffic spikes.

To reduce migration risk, SourceFuse used AWS Schema Conversion Tool (AWS SCT) and AWS Database Migration Service (AWS DMS) to assess schema complexity and automate large portions of the conversion process. The tools identified database objects that could be converted automatically, required light modification, or needed manual intervention, helping the team plan the migration with greater confidence. The modernization was supported through AWS funding programs, such as AWS Optimization and Licensing Assessment (AWS OLA) and Microsoft Modernization Program (MMP), which helped offset assessment and implementation costs and reduced the financial risk of replatforming.

In parallel, the company replaced its linear, SQL-based ETL jobs with distributed workflows built on AWS Glue and orchestrated using Amazon EventBridge. Previously, ingestion and transformation processes ran synchronously in fixed batches, limiting throughput. With AWS Glue-based distributed processing, Tuned Global can process multiple music catalog ingestion jobs simultaneously and automatically scale compute resources depending on catalog size. “Instead of having engineers constantly adjusting compute during ingestion peaks, we now rely on infrastructure that scales automatically,” Bilal says.

By removing the database bottleneck and modernizing its ETL processes, Tuned Global significantly increased ingestion throughput. The company expanded its ingestion capacity from 2 million to 20 million tracks per day when onboarding new clients and can ETL up to 10 million tracks daily during large onboarding events. As a result, customer onboarding timelines for major music catalogs were reduced by about 90 percent, from as long as 2 weeks to 1–2 days.

The platform achieved 3–5 times faster database query performance and now supports up to 10,000 read and write operations per second. At the application layer, it can scale from 1 million to 10 million API requests per minute without slowing response times, while maintaining sub-200 millisecond delivery standards for enterprise customers.

The modernization also delivered higher operational efficiency. Tuned Global reduced infrastructure costs by 33 percent and decreased human intervention in ingestion and scaling workflows by approximately 25 percent. Engineers no longer manually pre-scale resources or monitor database limits during traffic spikes.

“Moving to Amazon Aurora PostgreSQL gave us the scalability we needed to accelerate ingestion and customer onboarding while maintaining the performance standards our enterprise clients expect,” Bilal concludes.

Sourcefuse is a leading cloud, AI, and data platforms partner who help organizations modernize with confidence. As an AWS Premier Tier Services Partner with multiple competencies across AI, migration, SaaS, DevOps, healthcare, and modernization, we bring deep technical credibility alongside proven delivery expertise.