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Gatling is an open-source load testing tool for web applications and APIs, designed for high-performance, scriptable scenarios and real-time metrics. It simulates large numbers of users to measure throughput, latency and system behavior under stress. Gatling integrates with CI and supports scalable distributed execution.
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Gatling is an open-source load testing tool for web applications and APIs. It simulates virtual users, measures throughput and latency, and fits into automated CI pipelines.
Stéphane Landelle started Gatling in 2012 as an open-source project while serving as CTO at eBusiness Information; the first stable release was published on 13 January 2012. In 2015, Gatling Corp was created to continue the project and later provide commercial additions such as Gatling Enterprise.
Think of Gatling as a programmable load machine. A simulation defines user journeys and requests, an injection profile decides how many virtual users start and when, and the asynchronous engine processes the load efficiently. During execution it collects metrics; afterward Gatling produces reports that help compare bottlenecks and regressions.
Applications are tested under defined load to expose performance, stability, and scalability characteristics.
Gatling generates artificial user traffic that reproduces typical interactions at scale.
A simulation describes the test flow, parameters, and intended behavior as code.
The profile determines how load is distributed over time and with what intensity it is applied.
Throughput, latency, and distribution measures make results traceable and comparable.
Gatling is useful for repeatable performance tests of web and API systems, especially before releases, in CI, or for peak-load scenarios. It helps verify changes as regressions and observe time behavior under stress. Its limits are realism and context: the workload model, test data, infrastructure, and measurement point shape the result, and good test results do not replace production experience.
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