The correct answer is C. Specify Amazon CloudWatch as the destination for the access logs. Export the CloudWatch logs to an Amazon S3 bucket. Use Amazon Athena to query the logs and to filter the logs by host.

According to the AWS documentation1, AWS WAF offers logging for the traffic that your web ACLs analyze. The logs include information such as the time that AWS WAF received the request from your protected AWS resource, detailed information about the request, and the action setting for the rule that the request matched. You can send yourlogs to an Amazon CloudWatch Logs log group, an Amazon Simple Storage Service (Amazon S3) bucket, or an Amazon Kinesis Data Firehose.

To create a log analysis solution for the AWS WAF web ACLs, you can use Amazon Athena, which is an interactive query service that makes it easy to analyze data in Amazon S3 using standard SQL2. You can use Athena to query and filter the AWS WAF logs by host or any other criteria. Athena is serverless, so there is no infrastructure to manage, and you pay only for the queries that you run.

To use Athena with AWS WAF logs, you need to export the CloudWatch logs to an S3 bucket.You can do this by creating a subscription filter that sends your log events to a Kinesis Data Firehose delivery stream, which then delivers the data to an S3 bucket3.Alternatively, you can use AWS DMS to migrate your CloudWatch logs to S34.

After you have exported your CloudWatch logs to S3, you can create a table in Athena that points to your S3 bucket and use the AWS service log format that matches your log schema5. For example, if you are using format for your AWS WAF logs, you can use the AWSSerDe serde. Then you can run SQL queries on your Athena table and filter the results by host or any other field in your log data.

Therefore, this solution meets the requirements of creating a log analysis solution for the AWS WAF web ACLs with the most operational efficiency. This solution does not require setting up any additional infrastructure or services, and it leverages the existing capabilities of CloudWatch, S3, and Athena.

The other options are incorrect because:

A. Specifying Amazon Redshift as the destination for the access logs is not possible, because AWS WAF does not support sending logs directly to Redshift. You would need to use an intermediate service such as Kinesis Data Firehose or AWS DMS to load the data from CloudWatch or S3 to Redshift.Deploying the Amazon Athena Redshift connector is not necessary, because you can query Redshift data directly from Athena without using a connector6. This solution would also incur additional costs and operational overhead of managing a Redshift cluster.

B. Specifying Amazon CloudWatch as the destination for the access logs is possible, but using Amazon CloudWatch Logs Insights to design a query to filter the logs by host is not efficient or scalable.CloudWatch Logs Insights is a feature that enables you to interactively search and analyze your log data in CloudWatch Logs7.However, CloudWatch Logs Insights has somelimitations, such as a maximum query duration of 20 minutes, a maximum of 20 log groups per query, and a maximum retention period of 24 months8. These limitations may affect your ability to perform complex and long-running analysis on your AWS WAF logs.

D. Specifying Amazon CloudWatch as the destination for the access logs is possible, but using Amazon Redshift Spectrum to query the logs and filter them by host is not efficient or cost-effective.Redshift Spectrum is a feature of Amazon Redshift that enables you to run queries against exabytes of data in S3 without loading or transforming any data9. However, Redshift Spectrum requires a Redshift cluster to process the queries, which adds additional costs and operational overhead.Redshift Spectrum also charges you based on the number ofbytes scanned by each query, which can be expensive if you have large volumes of log data10.