API Gateway to DynamoDB - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ Architecture

intermediate

Design flow of a request from API Gateway to DynamoDB

Which option correctly describes the flow of a read request from an API Gateway to DynamoDB in a serverless architecture?

A API Gateway receives the request, triggers a Lambda function which queries DynamoDB and returns the result to API Gateway, which then responds to the client.

B API Gateway directly queries DynamoDB and returns the result to the client without any intermediate processing.

C DynamoDB pushes data to API Gateway which then sends it to the client without any request from API Gateway.

D API Gateway stores data temporarily and then asynchronously sends it to DynamoDB without client waiting.

💡 Hint

Think about how API Gateway interacts with backend services in a serverless setup.

API Gateway acts as the front door and triggers Lambda functions to interact with DynamoDB. It does not directly query DynamoDB.

❓ scaling

intermediate

Handling high read traffic from API Gateway to DynamoDB

You expect a sudden spike in read requests through API Gateway to DynamoDB. Which approach best helps handle this load without throttling?

A Disable DynamoDB Auto Scaling and rely on manual capacity increases only.

B Increase API Gateway timeout to allow longer waits for DynamoDB responses.

C Use API Gateway to batch all requests into one large DynamoDB write operation.

D Enable DynamoDB Auto Scaling for read capacity and use API Gateway caching to reduce direct calls.

💡 Hint

Think about how to reduce load on DynamoDB and automatically adjust capacity.

Auto Scaling adjusts capacity based on traffic. API Gateway caching reduces repeated calls, lowering load on DynamoDB.

❓ tradeoff

advanced

Choosing between direct DynamoDB access and Lambda proxy integration

What is a key tradeoff when choosing to let API Gateway directly access DynamoDB versus using a Lambda function as a proxy?

A Direct access reduces latency but limits request validation and complex logic; Lambda adds flexibility but increases latency.

B Direct access increases cost significantly; Lambda is always cheaper regardless of usage.

C Lambda cannot access DynamoDB securely; direct access is the only secure method.

D Direct access requires writing custom SDKs; Lambda uses built-in AWS SDKs automatically.

💡 Hint

Consider flexibility versus speed in request handling.

Direct access is faster but less flexible. Lambda allows validation, transformation, and complex logic but adds latency.

🧠 Conceptual

advanced

Understanding eventual consistency in DynamoDB with API Gateway

When API Gateway triggers a read from DynamoDB, which consistency model can cause the client to see stale data?

A DynamoDB does not support consistency models; API Gateway handles consistency.

B Strongly consistent reads can return stale data; eventually consistent reads always return the latest data.

C Eventually consistent reads can return stale data; strongly consistent reads always return the latest data.

D Both eventually and strongly consistent reads always return the latest data.

💡 Hint

Think about how DynamoDB consistency models affect read freshness.

Eventually consistent reads may lag behind writes, causing stale data. Strongly consistent reads always reflect the latest writes.

❓ estimation

expert

Estimating capacity for API Gateway to DynamoDB writes

Your API Gateway receives 10,000 write requests per minute, each writing 1 KB item to DynamoDB. What is the minimum write capacity units (WCUs) needed if each WCU supports 1 KB per second?

A 10,000 WCUs

B 167 WCUs

C 600 WCUs

D 1,000 WCUs

💡 Hint

Calculate requests per second and relate to WCU definition.

10,000 writes/min = 167 writes/sec. Each WCU supports 1 write/sec of 1 KB, so 167 WCUs needed.