Efficient data processing with AWS Lambda and DynamoDB: Handling timeouts and scalability issues
I am building a serverless application using AWS Lambda and DynamoDB. The application processes a large amount of incoming data, performs some transformations, and then stores the results back into DynamoDB. However, I am encountering issues with Lambda function timeouts and scalability as the data volume increases. Specifically, the Lambda functions often exceed the maximum execution time, and the DynamoDB read/write capacity units are sometimes insufficient to handle the load.