The N+1 query problem is the silent killer of scalable applications. It lurks in loops, hiding behind ORM abstractions, only revealing itself when production traffic spikes and database CPU utilization hits 100%.
The Limits of Dynamic Testing
Traditionally, teams try to catch N+1 queries using APM tools like Datadog or New Relic in staging environments. The problem is that staging data rarely reflects production data. A loop over 5 items in staging is negligible; a loop over 50,000 items in production causes an outage.
AST Flow Tracing
SudarshanAI's Deep Scanner approaches this statically. By generating the Abstract Syntax Tree (AST) of your Node.js or Python backend, the Scanner traces database query calls inside iterative structures. If it sees `prisma.user.findMany()` feeding into a loop that calls `prisma.post.findMany({ where: { userId } })`, it instantly flags an N+1 condition.
With deterministic AST analysis, you don't need traffic to find performance bottlenecks. You just need code.