Load testing

Load testing, also known as capacity testing, is a performance testing technique that evaluates how a system behaves as the demands placed upon it are progressively increased, with the aim of establishing the maximum operational capacity the system can sustain while still meeting its performance requirements.

By simulating realistic and increasingly heavy workloads — such as growing numbers of concurrent users, rising transaction rates, or escalating data throughput — load testing helps teams identify the point at which performance begins to degrade, where bottlenecks emerge, and whether the system can scale to meet anticipated demand. The results inform decisions about infrastructure sizing, architectural changes, and capacity planning.

A closely related technique is [volume testing], which focuses specifically on how the system handles the processing of large quantities of data rather than high levels of concurrent activity. Where load testing might simulate thousands of simultaneous users interacting with an application, volume testing is more concerned with what happens when the application is asked to read, write, or process exceptionally large datasets — checking for issues such as memory exhaustion, slow query performance, or unexpected failures as data volumes grow.

Together, load testing and volume testing give a comprehensive picture of a system’s [performance] at scale, ensuring it can cope with both the breadth of user demand and the depth of data it may be required to handle.