A video-sharing company stores its videos in an Amazon S3 bucket. The company needs to analyze user access patterns such as the number of users who access a specific video each month. Which solution…

Loading S3 access logs into an Amazon Aurora relational database would require substantial development effort for schema design, table creation, and building an ETL process to parse and ingest the log data.

Enabling Amazon S3 server access logging provides detailed records of all requests made to the S3 bucket, capturing user access information. Amazon Athena is a serverless query service that can directly query these S3 access logs using standard SQL, eliminating the need for complex ETL processes or data loading into a separate database, which significantly reduces development effort for analyzing access patterns.

Invoking an AWS Lambda function for every S3 object access event would generate a massive number of invocations for a video-sharing company, leading to prohibitively high costs and significant development effort to process and aggregate the event data efficiently.

Recording every S3 object access event in Amazon CloudWatch Logs would incur high ingestion and storage costs, and analyzing complex access patterns directly within CloudWatch Logs is less flexible and efficient than using Amazon Athena for structured SQL queries.