A hybrid environment has EC2 instances in a VPC that send application logs to CloudWatch and read data from on-premises relational databases. The company needs near-real-time visibility into which EC2 instances are connected to the databases and already uses Splunk on premises for monitoring. How should a solutions architect forward the necessary network log traffic to Splunk to meet these requirements?

The correct solution leverages VPC Flow Logs to capture network traffic, including connections to on-premises databases. Sending these logs to CloudWatch Logs allows for integration with other AWS services. A CloudWatch Logs subscription filter can then forward these logs directly to Amazon Kinesis Data Firehose. Kinesis Data Firehose is ideal for delivering streaming data to destinations like Splunk. The pre-processing Lambda function within Firehose is crucial for transforming the raw CloudWatch Logs data into a format Splunk can readily ingest, ensuring individual log events are properly extracted. The first incorrect option involves periodic S3 exports and Splunk pulling, which does not meet the "near-real-time" requirement. The third option is overly complex, resource-intensive, and focuses on database request logging rather than network flow, and also doesn't meet near-real-time needs. The fourth option uses Kinesis Data Analytics for anomaly detection, which is not the primary requirement; the goal is to forward raw network logs for visibility, not to perform real-time analytics and then forward only the results.