A company has several Amazon EC2 instances sitting behind an Application Load Balancer (ALB). The company wants its IT Infrastructure team to analyze the IP addresses coming into the company's ALB…

Copying 1TB of daily log data into Amazon Redshift for infrequent access is expensive and inefficient due to storage costs, the ETL process, and the compute required for data that is not frequently queried. This also incurs significant maintenance overhead.

Using Amazon EMR and Apache Hive to query S3 data requires managing an EMR cluster, which introduces operational overhead and does not align with the 'minimal maintenance' requirement for infrequent queries compared to serverless options.

Amazon Athena is a serverless query service that can query S3 data directly, offering scalability, cost-effectiveness (pay-per-query), and minimal maintenance. While a strong contender, Redshift Spectrum offers similar benefits and can be preferred if there's an existing Redshift environment or specific integration needs, leveraging Redshift's query optimizer.

Amazon Redshift Spectrum allows you to query data directly in Amazon S3 using familiar SQL, without loading it into Redshift itself. This approach is highly scalable, cost-effective as you pay only for the data scanned, and requires minimal maintenance as it leverages a Redshift cluster's compute while leaving data in S3, making it ideal for infrequent analysis of large, evolving log datasets.