As traffic and database demand are expected to grow tenfold, a Node.js web app team anticipates the need to scale their SQL query handling from hundreds of millions to billions daily, requiring pinpointing slow queries to prevent performance bottlenecks. The team initially considered using Datadog for tracing but found it cost-prohibitive and ineffective for their background worker-heavy load. They also attempted monkey patching, which proved impractical. Ultimately, they implemented call site tagging, a solution where SQL queries are tagged with user-defined strings indicating their origin in the codebase, improving traceability, legibility, and cost-effectiveness. Despite challenges with the TypeORM library, they achieved nearly 100% coverage by wrapping all TypeORM calls in a query builder API, adding tagging, and using linting rules to ensure compliance. This approach allowed them to quickly identify and optimize problem areas, preparing them for anticipated user growth and database scaling, while also considering further improvements like supporting tagging across all TypeORM APIs and building internal tools to prevent untagged queries.