A company is designing a serverless application using Amazon API Gateway, AWS Lambda, and Amazon DynamoDB. The application must handle sudden, massive spikes in traffic (up to 100,000 requests per second) without dropping requests or overwhelming the database. The business requires that all requests are eventually processed, even if delayed during peaks. Which combination of architectural patterns should be used? (Select TWO)

Answer options:

Implement an Amazon SQS queue between API Gateway and Lambda to buffer requests.

Configure DynamoDB in On-Demand capacity mode to handle unpredictable workloads.

Enable API Gateway caching to serve all requests directly from the cache.

Increase the Lambda concurrency limit to 100,000 to process all requests synchronously.

Use AWS Step Functions Express Workflows instead of Lambda for faster execution.

Configure DynamoDB Provisioned capacity with Auto Scaling set to 90% utilization.

How to approach this question

Look for decoupling/buffering patterns for the compute layer and auto-scaling/on-demand patterns for the database layer.

Full Answer

To handle massive, sudden spikes without dropping requests, decoupling the architecture is essential. API Gateway can integrate directly with Amazon SQS to buffer incoming requests. Lambda can then poll the queue at a controlled rate. For the database, DynamoDB On-Demand mode is designed specifically for unpredictable, spiky workloads.

Common mistakes

Trying to scale synchronous compute (Lambda concurrency) instead of decoupling with a queue.

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