Redis Pub/Sub drops messages the moment a subscriber disconnects. Redis Streams with consumer groups gives you at-least-once delivery, horizontal scaling, and failure recovery without adding Kafka to your stack.
A single poison message crashes your worker, the broker redelivers it, and the crash loop takes down your entire pipeline. Here is the DLQ pattern that separates bad messages from good ones, with working code for RabbitMQ and the replay strategy that turns a dead letter into a recovered system.
Kafka and RabbitMQ both move messages and are not interchangeable. One is a distributed log, the other is a message router. Picking the wrong one means a year of fighting the abstractions. Here is the workload-based decision tree, the operational realities of each, and the rare case where you need both.