How does the batch size affect autoscaling? And Everything you need to know >>

ABHAY K SINGH

Date :- Sept 11, 2023 Day :- Monday

amazon aw

When triggering AWS Lambda functions from an event source like Amazon SQS, the batch size parameter can significantly impact how Lambda autoscales your functions. 

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Batch size refers to the maximum number of messages that Lambda will retrieve from the queue and pass to your function as a single invoke request.

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A larger batch size means fewer invokes and thus fewer Lambda scaling events. This can reduce costs and latency compared to invoking Lambda for each message.

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However, each Lambda function invocation has some overhead for initializing a new execution environment.  

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A good batch size aims for a balance between utilizing Lambda’s parallel processing and avoiding excessive initialization overhead.  

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To compensate, you can configure a higher maximum scaling limit for your function if you’re using a large batch size.  

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Reduce costs by minimizing the number of invoke

– Improve latency by amortizing initialization overhead across multiple message

it can also limit autoscaling if you don’t adjust the maximum scaling limit to match your batch size.

Summary  :-

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