A company built a data ingestion pipeline that uses Amazon Kinesis Data Firehose to send ecommerce sales transactions into Amazon OpenSearch Service. The Firehose buffer interval is set to 60 seconds. An OpenSearch linear model produces real-time sales forecasts that appear on an OpenSearch dashboard. The company requires sub-second latency for the real-time dashboard. Which architectural change will achieve that requirement?

The correct answer is to set the Firehose stream to use zero buffering and tune the batch size used by PutRecordBatch. This directly addresses the sub-second latency requirement by minimizing the delay introduced by Firehose's buffering. Zero buffering means data is delivered as quickly as possible. Tuning PutRecordBatch ensures efficient, near real-time ingestion into OpenSearch without excessive overhead. Replacing Firehose with AWS DataSync is incorrect because DataSync is designed for large-scale data transfer between storage services, not real-time streaming to OpenSearch. Increasing the Firehose buffer interval would worsen latency, not improve it. Replacing Firehose with an Amazon SQS queue is incorrect because SQS is a message queuing service, not a direct data delivery service to OpenSearch, and would require additional components to process and push data, increasing complexity and potentially latency.