What is the MOST operationally efficient solution that meets these requirements?
Create a table in Amazon Athena for AWS CloudTrail logs. Create a query for the relevant information.
Enable ALB access logging to Amazon S3. Create a table in Amazon Athena, and query the logs.
Enable ALB access logging to Amazon S3. Open each file in a text editor, and search each line for the relevant information.
Use Amazon EMR on a dedicated Amazon EC2 instance to directly query the ALB to acquire traffic access log information.
Explanations:
Using CloudTrail logs is not the best method for analyzing ALB traffic patterns, as CloudTrail primarily logs API calls and not HTTP(S) traffic data.
Enabling ALB access logging to S3 and using Amazon Athena to query the logs provides an efficient, scalable, and cost-effective solution to analyze traffic patterns. Athena can quickly query large amounts of data stored in S3.
Opening each log file in a text editor is not operationally efficient for analyzing large volumes of data and would be time-consuming and error-prone.
Using Amazon EMR on a dedicated EC2 instance is unnecessarily complex and costly for simply analyzing ALB access logs. Athena provides a simpler and more cost-effective solution.
In my opinion, the answer is:
Enable ALB access logging to Amazon S3. Create a table in Amazon Athena, and query the logs.