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What is Gatling's significant architectural advantage for generating high load compared to a naive thread-per-user testing approach?
Questions in this quiz
What is Gatling's significant architectural advantage for generating high load compared to a naive thread-per-user testing approach?
What is the purpose of Gatling's "feeders" (e.g. `csv("users.csv").random`)?
What is the purpose of "checks" (`.check(status.is(200))`) in a Gatling scenario?
What does an "injection profile" (e.g. `rampUsers(1000).during(60.seconds)`) control in a Gatling simulation?
What is a common reason a performance test might pass functionally (all checks succeed) but still reveal a problem worth investigating?
What does Gatling's HTML report (generated after a simulation run) typically show?
What is the practical benefit of Gatling scenarios being written as code (Scala/Java/Kotlin DSL) rather than recorded/configured purely through a GUI?
Why do performance testers typically care more about response time percentiles (like p95, p99) than the average response time?
Why is it important to run a load test from a machine (or set of machines) with sufficient network bandwidth and CPU capacity, separate from the system under test?
What protocols beyond plain HTTP can Gatling be used to load test?
What is the relationship between throughput (requests/second) and response time as concurrency increases during a load test, in a system approaching its capacity limit?