Which solution will meet these requirements MOST cost-effectively?
Configure Route 53 to export log data to Amazon S3. Configure an S3 Lifecycle policy that deletes objects in the target S3 bucket that are older than 1 year.
Configure Route 53 to export log data to Amazon S3. Configure an AWS Lambda function to run every hour to delete log files that are older than 1 year.
Configure Route 53 to export log data to Amazon CloudWatch Logs. For the target CloudWatch Logs log group, set the retention period to 1 year.
Configure Route 53 to export log data to Amazon CloudWatch Logs. Use CloudWatch Logs Insights to identify and delete log entries that are older than 1 year.
Explanations:
This option effectively uses Amazon S3 for log storage, which is highly durable and cost-effective. Configuring an S3 Lifecycle policy to delete objects older than 1 year automates the cleanup process without requiring additional management overhead.
While this option also uses Amazon S3 for log storage, it introduces unnecessary complexity by requiring an AWS Lambda function to delete logs. This adds operational overhead and cost due to Lambda invocations, making it less efficient than using an S3 Lifecycle policy.
Although this option leverages CloudWatch Logs, which can store logs with a configurable retention period, CloudWatch Logs is generally more expensive than S3 for long-term storage. Setting the retention period to 1 year does meet the requirement, but it is not the most cost-effective solution.
This option suggests using CloudWatch Logs and requires manual intervention through CloudWatch Logs Insights to delete logs older than 1 year. This approach adds complexity and operational overhead compared to automated solutions, making it less desirable in terms of cost-effectiveness.
I organize that the answer is:
Configure Route 53 to export log data to Amazon S3. Configure an S3 Lifecycle policy that deletes objects in the target S3 bucket that are older than 1 year.