AWS Certified Solutions Architect – Associate (SAA-C03) — Question 145
A company is designing an application where users upload small files into Amazon S3. After a user uploads a file, the file requires one-time simple processing to transform the data and save the data in JSON format for later analysis.
Each file must be processed as quickly as possible after it is uploaded. Demand will vary. On some days, users will upload a high number of files. On other days, users will upload a few files or no files.
Which solution meets these requirements with the LEAST operational overhead?
Answer options
- A. Configure Amazon EMR to read text files from Amazon S3. Run processing scripts to transform the data. Store the resulting JSON file in an Amazon Aurora DB cluster.
- B. Configure Amazon S3 to send an event notification to an Amazon Simple Queue Service (Amazon SQS) queue. Use Amazon EC2 instances to read from the queue and process the data. Store the resulting JSON file in Amazon DynamoDB.
- C. Configure Amazon S3 to send an event notification to an Amazon Simple Queue Service (Amazon SQS) queue. Use an AWS Lambda function to read from the queue and process the data. Store the resulting JSON file in Amazon DynamoDB.
- D. Configure Amazon EventBridge (Amazon CloudWatch Events) to send an event to Amazon Kinesis Data Streams when a new file is uploaded. Use an AWS Lambda function to consume the event from the stream and process the data. Store the resulting JSON file in an Amazon Aurora DB cluster.
Correct answer: C
Explanation
Option C is correct because it leverages AWS Lambda, which automatically scales with demand and has minimal operational overhead. Options A and D involve more complex infrastructure with Amazon EMR and Amazon Kinesis Data Streams, respectively, which require more management and configuration. Option B uses Amazon EC2, which also adds operational overhead compared to the serverless architecture of option C.