An on-premises environment exposes audit logs via an HTTP endpoint. The company wants an automated, low-operational-effort solution to regularly ingest large volumes of these logs into AWS for storage and queries. Which solution best meets the requirement?

AWS DataSync is ideal for transferring large volumes of data from on-premises environments to AWS storage services like Amazon S3. Its managed nature ensures low operational effort and handles network interruptions efficiently. Storing logs in S3 provides durable, scalable, and cost-effective storage. Amazon Athena can directly query data in S3 using standard SQL, making it a powerful and serverless solution for analyzing the ingested logs without needing to load them into a database. Exporting logs to RDS is less suitable for large volumes of unstructured or semi-structured logs, and RDS is a relational database not optimized for raw log storage and querying. A Lambda function polling an HTTP endpoint and pushing to CloudTrail Lake is an unnecessary intermediary step for general audit logs and CloudTrail Lake is specifically for CloudTrail logs, not arbitrary on-premises audit logs. Installing the CloudWatch agent requires installation and management on each on-premises server, which is more operational overhead than DataSync, and CloudWatch Logs Insights is powerful but DataSync to S3 with Athena offers more flexibility for large-scale, diverse log analysis.