Your order processing service runs on SQS.
Normal load: 200 orders/min. Consumers keep up fine.
Then Black Friday hits. Producers start pushing 4,000 orders/min. Queue depth climbs to 80,000 messages in 20 minutes. Your downstream DB is at 95% CPU. Consumers are falling behind and you're watching the queue grow in real time.
You need to handle this backpressure. What do you do?
A) Scale consumers horizontally — add more Lambda functions / EC2 workers to chew through the backlog faster.
B) Set a visibility timeout and route failures to a dead-letter queue to protect against poison pills.
C) Rate-limit producers at the source — use a token bucket or sliding window to cap how fast messages enter the queue.
D) Switch to SQS delay queues — defer message visibility to spread out delivery and reduce consumer pressure.
Three of these are real patterns engineers reach for. Only one actually solves backpressure.
Pick one — A, B, C, or D — and tell me why. Full breakdown in the comments.
If this made you second-guess your instinct, share it — someone on your team is designing this right now.