A company needs to analyze access logs for an Application Load Balancer (ALB) that routes traffic to the company’s online login portal. The company must use visualizations to identify login attempts by bots from a known list of IP addresses. Which solution will meet these requirements?

The correct solution leverages Amazon S3 for cost-effective log storage, Amazon Athena for serverless SQL querying of the logs, and Amazon QuickSight for creating interactive visualizations. This combination is ideal for analyzing large volumes of log data and identifying patterns like bot login attempts from specific IP addresses. Storing logs directly in Amazon CloudWatch Logs (option 1) is possible, but CloudWatch Logs Insights, while good for querying, has more limited visualization capabilities compared to QuickSight, and direct ALB to CloudWatch Logs integration for access logs isn't the primary or most scalable method. Sending logs directly to Amazon Redshift (option 2) would involve unnecessary data warehousing overhead and cost for this specific use case, as Athena can query S3 directly. Amazon OpenSearch Service (option 3) is a powerful search and analytics engine, but for ad-hoc querying and visualization of existing S3-stored logs, Athena and QuickSight offer a more serverless and often more cost-effective approach without needing to manage an OpenSearch cluster.