Which solution will meet these requirements with the LEAST operational overhead?
Create an Amazon CloudWatch Logs log group. Configure the appropriate AWS WAF web ACL to send log messages to the log group. Instruct the operations team to create CloudWatch metric filters.
Create an Amazon OpenSearch Service cluster and appropriate indexes. Configure an Amazon Kinesis Data Firehose delivery stream to stream log data to the indexes. Use OpenSearch Dashboards to create filters and widgets.
Create an Amazon S3 bucket for the log output. Configure AWS WAF to send log outputs to the S3 bucket. Instruct the operations team to create AWS Lambda functions that detect each desired log message pattern. Configure the Lambda functions to publish to an Amazon Simple Notification Service (Amazon SNS) topic.
Create an Amazon S3 bucket for the log output. Configure AWS WAF to send log outputs to the S3 bucket. Use Amazon Athena to create an external table definition that fits the log message pattern. Instruct the operations team to write SQL queries and to create Amazon CloudWatch metric filters for the Athena queries.
Explanations:
This option allows the operations team to analyze AWS WAF logs in CloudWatch Logs with minimal setup. By configuring AWS WAF to send logs to a CloudWatch Logs log group, the operations team can easily create metric filters for specific patterns without additional infrastructure. This solution provides a direct and efficient way to create alarms and requires the least operational overhead.
While Amazon OpenSearch Service can be used for analyzing logs, it requires more operational overhead to set up and maintain compared to CloudWatch Logs. The need to manage an OpenSearch cluster and Kinesis Data Firehose introduces additional complexity, making this solution less optimal for the given requirements.
This option involves using an S3 bucket and AWS Lambda functions to detect log patterns. This requires more operational management, including the maintenance of Lambda functions and additional configurations for SNS. It also lacks the straightforward alarm capabilities that CloudWatch provides, increasing operational overhead.
Although using S3 and Amazon Athena for querying logs can be effective, it involves more steps for the operations team to create and manage SQL queries and integrate with CloudWatch metric filters. This approach introduces additional complexity and latency compared to the direct integration available in option A.