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.

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