How does Rails handle large-scale system backpressure in distributed pipelines?

Rails handles backpressure using queue limits, rate limiting, and adaptive consumer scaling.

Backpressure occurs when producers generate more data than consumers can process. Rails systems mitigate this using queue size monitoring, rate limiting at API gateways, and autoscaling background workers. Kafka-style systems naturally support backpressure through partition lag. Without proper control, systems risk memory overflow or cascading failures.