AWS Lambda Concurrent Executions Limits optimization guide as Expected in Production Environment
I recently switched to I'm relatively new to this, so bear with me... I'm currently running an AWS Lambda function that processes events from an SQS queue. My function is set to handle a maximum of 10 concurrent executions, but I noticed that during peak times, it seems to exceed this limit, leading to throttling and performance optimization. I have configured the reserved concurrency for the Lambda function in the AWS Management Console as follows: ```json { "FunctionName": "MySQSProcessor", "Concurrency": { "ReservedConcurrentExecutions": 10 } } ``` However, I am still receiving the following behavior messages in CloudWatch logs: ``` Task timed out after 3.00 seconds Rate exceeded ``` To troubleshoot, I've checked the SQS queue and verified the messages are being sent correctly. I also ensured that the Lambda function’s timeout setting is sufficient (it’s set to 5 seconds), but it seems that when the number of messages spikes, the Lambda invocations continue to increase beyond the set limit. I've also implemented a dead-letter queue (DLQ) to catch any failed messages, but I want to understand why the concurrent execution limit isn't being enforced as expected. Are there any best practices or additional settings I should consider when using AWS Lambda with SQS to manage concurrency properly? I've looked into adjusting the SQS batch size, which is currently set to the default of 10, but that hasn’t resolved the scenario either. Any ideas what could be causing this?