Q: 10
A developer has designed an application to store incoming data as JSON files in Amazon S3 objects.
Custom business logic in an AWS Lambda function then transforms the objects, and the Lambda
function loads the data into an Amazon DynamoDB table. Recently, the workload has experienced
sudden and significant changes in traffic. The flow of data to the DynamoDB table is becoming
throttled.
The developer needs to implement a solution to eliminate the throttling and load the data into the
DynamoDB table more consistently.
Which solution will meet these requirements?
Options
Discussion
A for sure. SQS acts as a buffer so sudden spikes get smoothed before Lambda tries writing to DynamoDB. Seen similar in other AWS exam practice sets, so pretty confident here. Let me know if you read it differently.
B or C here. Both seem like decent ways to handle the scaling.
Its A for this one. Using SQS between transform and load steps helps buffer spikes so DynamoDB doesn't get overwhelmed all at once. Not 100% sure since I haven't seen this exact scenario before, but it matches similar practice ones. Anyone agree?
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