Choosing Between Open and Closed Workload Models in Gatling
Learn how to choose between Open and Closed workload models in Gatling to avoid coordinated omission and simulate realistic user traffic for APIs and internal systems.
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Learn how to choose between Open and Closed workload models in Gatling to avoid coordinated omission and simulate realistic user traffic for APIs and internal systems.
Data‑driven authentication tests in Gatling are easy with CSV feeders. Learn how to set up per‑user feeders, avoid contention, and validate your results in this practical guide.
Learn how Gatling's Closed Model maintains fixed concurrent virtual users for predictable load testing, and when to use it instead of the Open Model.
Learn how to choose between injection profiles, throttling, and pacing in Gatling to maintain a steady target RPS without distorting latency measurements.
High response times with a calm target server often mean your k6 load generator is saturated. Learn how to diagnose VU memory pressure and right-size your test.
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.
Fail CI pipelines automatically when k6 load tests breach latency or error‑rate SLOs by defining thresholds, using abortOnFail, and tagging requests. This guide shows how to set up, run, and verify thresholds in CI.