Q28 — AWS DOP-C02 Ch.3

Question 28 of 100 | ← Chapter 3

A DevOps engineer manages several legacy applications, each generating different log formats. The engineer wants to first standardize the formats and then write them to Amazon S3 for querying and analysis.

• A. Have the applications send their logs to an Amazon EMR cluster and normalize the logs before sending them to Amazon S3.
• B. Have the applications send their logs to Amazon QuickSight, then use the Amazon QuickSight SPICE engine to normalize the logs and perform analysis directly from Amazon QuickSight.
• C. Store the logs in Amazon S3 and use Amazon Redshift Spectrum to normalize the logs in-place.
• D. Use Amazon Kinesis Agent on each server to upload logs, and use Amazon Kinesis Data Firehose with an AWS Lambda function to normalize the logs before writing them to Amazon S3. ✓

Correct Answer: D. Use Amazon Kinesis Agent on each server to upload logs, and use Amazon Kinesis Data Firehose with an AWS Lambda function to normalize the logs before writing them to Amazon S3.

Explanation

D: Use Amazon Kinesis Agent on each server to upload logs, leveraging Amazon Kinesis Data Firehose and an AWS Lambda function for log normalization. This approach uses streaming processing for real-time data handling while avoiding the cost and overhead of managing additional clusters or services. Option A: Using Amazon EMR incurs higher costs due to cluster maintenance and operation, making it less economical for small-scale log processing. Option B: Amazon QuickSight is primarily for visualization and analysis, not log normalization, and may incur unnecessary costs. Option C: Using Amazon Redshift Spectrum requires logs to be stored in S3 first but imposes performance requirements that may add complexity and cost.