Efficient message processing is crucial when handling large data volumes. By employing batching, distribution, and parallelization techniques, you can optimize the utilization of resources allocated to your AWS Lambda function.
Lambda continuously polls the event source and automatically invokes your function to process the retrieved data. Lambda makes more invocations of your function as the number of messages it reads from the event source increases.
To improve data processing throughput, you can configure event-source mapping batch window and batch size. These settings ensure that your function is invoked only when a sufficient number of messages have accumulated.
By processing messages in batches, rather than individually, you can improve throughput and optimize costs by reducing the number of polling requests to event sources and the number of function invocations.
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