AWS DevOps Engineer - Professional

By Amazon · Question Mode

QuestionQ39

Resilient Cloud Solutions

A company has deployed a new Amazon API Gateway API that retrieves item costs for the company’s online store. An AWS Lambda function backs the API and retrieves the data from an Amazon DynamoDB table. The API’s latency rises during peak usage periods each day. However, DynamoDB table-read latency remains constant throughout the day.

A DevOps engineer configures DynamoDB Accelerator (DAX) for the DynamoDB table, and API latency decreases throughout the day. The DevOps engineer then configures Lambda provisioned concurrency with a limit of two concurrent invocations. This change reduces latency during normal usage. However, the company still experiences greater latency during peak usage periods than during normal usage.

Which additional set of steps should the DevOps engineer take to achieve the LARGEST decrease in API latency?

Explanation

API Gateway caching returns cached endpoint responses without invoking the Lambda integration, reducing both backend calls and API-request latency for repeated item-cost lookups. Application Auto Scaling can manage Lambda provisioned concurrency on a schedule for predictable daily peaks or according to utilization, preventing a fixed provisioned concurrency value of two from being exhausted. DynamoDB read capacity is not the limiting factor because DynamoDB read latency is constant, and removing DAX would discard an existing latency improvement.

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