How does Kotlin behave under heavy GC pressure in production systems?

Kotlin does not control GC; it inherits JVM GC behavior, and performance depends on allocation patterns.

Under heavy GC pressure, Kotlin applications suffer not because of Kotlin itself but due to object allocation patterns created by lambdas, collections, and coroutines. Frequent short-lived objects trigger Minor GC cycles, while retained references can cause Full GC pauses. Coroutines reduce thread blocking but do not eliminate memory churn. In high-scale systems, engineers optimize by reducing allocations, using primitive collections, object pooling, and avoiding intermediate streams/sequences in hot paths.