DOP-C02 · Question #24
A video-sharing company stores its videos in Amazon S3. The company has observed a sudden increase in video access requests, but the company does not know which videos are most popular. The company…
The correct answer is B. Activate S3 server access logging. Use Amazon Athena to create an external table with the log. Explanation Option B is correct because enabling S3 server access logging natively captures all access patterns (including file-level requests and user counts) with minimal configuration, and Amazon Athena can directly query those logs stored in S3 using standard SQL without…
Question
A video-sharing company stores its videos in Amazon S3. The company has observed a sudden increase in video access requests, but the company does not know which videos are most popular. The company needs to identify the general access pattern for the video files. This pattern includes the number of users who access a certain file on a given day, as well as the number of pull requests for certain files. How can the company meet these requirements with the LEAST amount of effort?
Options
- AActivate S3 server access logging. Import the access logs into an Amazon Aurora database. Use
- BActivate S3 server access logging. Use Amazon Athena to create an external table with the log
- CInvoke an AWS Lambda function for every S3 object access event. Configure the Lambda
- DRecord an Amazon CloudWatch Logs log message for every S3 object access event. Configure a
How the community answered
(27 responses)- A4% (1)
- B74% (20)
- C7% (2)
- D15% (4)
Explanation
Explanation
Option B is correct because enabling S3 server access logging natively captures all access patterns (including file-level requests and user counts) with minimal configuration, and Amazon Athena can directly query those logs stored in S3 using standard SQL without requiring any data migration or infrastructure setup - making it the least-effort solution.
Why the distractors are wrong:
- Option A is wrong because importing logs into Amazon Aurora requires additional steps (provisioning a database, ETL processes), adding unnecessary complexity and effort compared to Athena's serverless, in-place querying.
- Option C is wrong because invoking a Lambda function on every S3 object access event introduces significant engineering overhead (writing code, managing invocations, storing results), making it far more effort-intensive than a simple logging + query solution.
- Option D is wrong because routing S3 events through CloudWatch Logs adds an unnecessary intermediary layer, increasing complexity and cost compared to directly querying S3 access logs with Athena.
Memory Tip
Think "Log it, Query it" - whenever a question asks about analyzing S3 access patterns with least effort, the winning combo is S3 Server Access Logging + Athena. Athena is serverless and queries logs where they live in S3, so there's no database to provision or code to write.
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