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Answer: Employ Amazon SQS with Lambda to manage write buffering to DynamoDB.
The correct answer is D: Employ Amazon SQS with Lambda to manage write buffering to DynamoDB. By integrating Amazon SQS, you can decouple the ingestion of user requests from the processing and storage, allowing the system to handle higher loads without losing any requests. SQS helps to buffer the requests and ensures reliable delivery to DynamoDB even when there are spikes in traffic or DynamoDB is throttled. The other options do not fully address the issue of handling high traffic and preventing loss of user requests. For instance, API Gateway throttling (A) would limit the number of requests accepted, which could result in lost requests. DAX (B) is a read-through cache for DynamoDB, which wouldn't help with buffering writes. Creating a secondary index (C) does not solve the problem of throughput limitations or request loss.
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A company's asynchronous API, deployed via Amazon API Gateway, and a Lambda function interfacing with Amazon DynamoDB, is experiencing availability issues despite budget-constrained throughput provisioning. How can a solutions architect mitigate request loss without affecting current users?
A
Implement API Gateway throttling with server-side limits.
B
Integrate DynamoDB Accelerator (DAX) with Lambda for write buffering to DynamoDB.
C
Establish a secondary DynamoDB index for the user request table.
D
Employ Amazon SQS with Lambda to manage write buffering to DynamoDB.
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