A company currently uses EC2 instances for a custom ingestion pipeline that sends on-prem server logs, mobile app logs, and IoT sensor data to S3 and OpenSearch Service. They want a new serverless pipeline that scales automatically and is cost-effective. Which architecture meets these requirements most economically?

The correct option is the most economical because it utilizes a single Kinesis Data Firehose delivery stream to fulfill both requirements: sending data to OpenSearch Service and backing up raw data to S3. This minimizes the number of AWS services and connections needed. Kinesis Data Firehose is serverless and scales automatically, meeting those requirements. The incorrect options involve creating multiple Firehose streams or introducing Kinesis Data Streams unnecessarily. Creating two Firehose streams (one for S3, one for OpenSearch) adds redundant resources. Using a Kinesis Data Stream as an intermediary before Firehose adds complexity and cost without providing significant benefit for this specific scenario, as Firehose can directly ingest data from sources and deliver to multiple destinations.