I'm not sure I get your problem. Would be nice if you could illustrate it with example project. By sequential you mean processing messages in order I suppose but for this you would need fifo queues or design the app differently, e.g. say you store the current processing state in db. When message2 arrives before message1 you check in db that message1 was not yet processed and you put message1 in another queue and have another lambda which will forward the message back to the original queue (then the receive count is 0 again), when message1 arrives next you process it and update db state so when next time you receive message2 you will know that you can process it already. You could also use the DLQ for that and the other lambda could pass messages from DLQ back to the original queue. Just an idea, don't know your particular case but maybe it works for you.
Ah no I wasn't talking about order but rather the regulation flow. So I want the messages to wait in the queue until the worker can process them but with SQS/Lambda the messages won't wait since they are experiencing throttling and will fail and will either be removed or go to the DLQ.
But I liked you technique on preserving order. I haven't tried it, maybe I will in the future.
Hmm.. I see. So maybe you could try the same technique here. When throttled message goes to DLQ you have a lambda function running in some scheduled interval which you set by experimenting with throttle rate, and this lambda will forward the message from DLQ back to original queue from which it could possibly be processed again and hopefully not throttled again.
I just created this repo and remembered of our discussion. This is how I managed to create a sequential processing pipeline with AWS SQS and Lambda on a Serverless project.
Let me know what you think! Thank you.
Nice :) I like it.
I tried to find out what happens to the CloudWatch event which is throttled, if it is retried or dropped but I could not see in docs, but I suppose it is more a problem of AWS what to do with high number of cumulated CloudWatch events which are continuously retried, rather than your problem, since setting of concurrency limit on Lambda to 1 provides that no more than 1 instance of this function will execute at certain time.
Nice wrap up. Thanks.
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