Scalability Testing
Scalability testing measures how well a system's performance holds up as load increases, and whether adding resources (more servers, more database capacity) actually produces a proportional performance improvement. It answers "can this grow," distinct from capacity testing's "what's the current maximum."
A system can have a high current capacity while scaling poorly — if doubling the server count only improves throughput by 20% instead of close to 100%, something in the architecture (a shared database bottleneck, a single point of serialization) is capping how far the system can actually scale, regardless of how much hardware gets thrown at it.
Testing this typically means measuring performance at multiple different scale points (1x, 2x, 4x infrastructure) and checking whether performance improves close to linearly — a system that scales well shows a roughly proportional relationship; one that doesn't reveals an architectural bottleneck worth investigating before committing to more infrastructure spend.
