Efficiently processing batched data using parallelization in AWS Lambda
Compute Blog
This article discusses how to efficiently process batched data using parallelization in AWS Lambda functions.
Specifically, the article covers:
- Overview of batching messages from event sources like SQS and Kinesis into Lambda functions
- Implementing parallel processing within Lambda execution environments to maximize resource utilization
- Ensuring background threads complete within the same invocation to avoid unexpected behavior
- Sample code for parallel processing using Node.js promises
- Testing results showing improved performance and reduced concurrency requirements
- Considerations like handling ordering and partial batch failures
- Conclusion emphasizing efficient resource utilization and tools like Powertools and Power Tuning
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