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Frameworks & web · #gatling
Learn how to choose between injection profiles, throttling, and pacing in Gatling to maintain a steady target RPS without distorting latency measurements.
Learn how to use Gatling HTTP response checks to create trust boundaries, preventing invalid data propagation and ensuring load test accuracy.
When Gatling KO% spikes during ramp-up with connect timeouts, connection refused, or too many open files while the target looks healthy, the issue is usually injector socket exhaustion or target accept-queue overflow.
Identical requests can make a Gatling load test look busy while measuring nothing. Choose a feeder strategy that matches your endpoint's uniqueness needs, and verify it in the simulation log.
Inject data into Gatling scenarios with a CSV feeder. Learn how to configure, stream, and avoid common pitfalls so your load tests run reliably and efficiently.
Learn how to shape the request rate of a Gatling test with the throttle injection profile, including setup, verification steps, and common recovery actions.
Learn how Gatling’s injection profiles let you shape traffic patterns, from sudden spikes to steady streams, and why the right choice matters for realistic load testing.
Open vs. Closed Injection in Gatling – a concise decision guide that maps constraints, compares profiles, explains trade‑offs, and shows a concrete simulation with validation steps.
Learn when to use Gatling’s open injection (constant arrival rate) versus closed injection (fixed concurrency), see a Scala DSL example, and understand the limits and pitfalls of each model.