OptiScale

A single request to an application can trigger hundreds of unnecessary database queries. A common cause is the N+1 problem: the code retrieves a list of records, then queries the database again for each item in a loop. Without appropriate indexes, those queries become even slower. The result is higher latency and greater resource use, especially in production systems serving many users. OptiScale is designed to help development teams find and address performance bottlenecks in production applications, with the goal of supporting projects across languages and frameworks. Users upload a project as a ZIP file to see detected issues, the relevant code, and proposed improvements. A guided Upload → Analyze → Optimize → Benchmark → Prove flow presents before-and-after code alongside throughput, latency, CPU, and memory comparisons, helping teams decide what to investigate first. OptiScale’s distinctive approach connects a detected problem, a reviewable fix, and its potential performance impact in one workflow. Instead of increasing infrastructure capacity without understanding the cause, teams can identify code that may generate excessive database queries. The current browser-based prototype analyzes Python/FastAPI projects using pattern-based rules and was developed with IBM Bob as a coding assistant. Support for additional languages and benchmarking against real production workloads are future development goals.