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Answer: Deploy multiple Lambda functions with limited concurrency and use DynamoDB Streams' shard management to distribute the load.
Option B is correct because it involves deploying multiple Lambda functions with controlled concurrency, which helps manage throughput and ensures data durability by leveraging DynamoDB Streams' shard management. Using a single Lambda function with unlimited concurrency (Option A) can lead to throttling and potential data loss. Processing streams directly in DynamoDB (Option C) is not feasible for complex processing. Using Kinesis Data Streams (Option D) is not necessary when DynamoDB Streams can fulfill the requirements.
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You are designing a data ingestion system that requires real-time processing of data from Amazon DynamoDB streams. The system must handle a high throughput and ensure that no data is lost during processing. Describe how you would implement a Lambda function to process these streams, including strategies for managing throughput and ensuring data durability.
A
Use a single Lambda function with unlimited concurrency to process the streams.
B
Deploy multiple Lambda functions with limited concurrency and use DynamoDB Streams' shard management to distribute the load.
C
Process the streams directly in DynamoDB without using Lambda.
D
Use Amazon Kinesis Data Streams instead of DynamoDB Streams for processing.
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