Celery can be backed by RabbitMQ, not sure if that's what you meant, but all of what you described can be abstracted away. I didn't have the same experiences with months taken to get up to speed. Moreover, at work RabbitMQ is probably our most stable underlying tool, perhaps toe to toe with Redis. And that's saying a lot, since I consider Redis to almost be a piece of art in how great of a tool it is.

Back to RabbitMQ though, we run a HA 2 node deployment (just one active writer) and have been for over 3 years, requiring minimal changes or any kind of maintenance whatsoever, has scaled to hundred plus queues, going from some with super high numbers of messages per second, some with only tens of messages per day. Some queues stay low and process fast, others are heavy jobs that get enqueued all at once and generate hundreds of thousands of jobs.

Sure, if you have a service that interacts with disks you should have automated a monitor that cover your IOPS consumption, but I don't see how that's specific to RabbitMQ, you should be doing this for all your instances.

All in all, these are two identic instances, one active, one failover, and in a world of Kafkas and Pulsars and understanding the ins and outs of SQS pricing and capacity allocation, RabbitMQ is a tool that I consider simple to administer and allows me to sleep at night.

Interesting how the same tool can evoke such different reactions, but whatever works - works.