An application processes millions of events in real time that arrive through an API. Which service allows multiple consumers to process the stream concurrently while being the most cost-effective?

Amazon Kinesis Data Streams is the most suitable and cost-effective option for processing millions of real-time events concurrently with multiple consumers. It allows multiple applications to consume the same stream of data independently and in parallel, providing high throughput and low latency. Kinesis Data Streams is designed for real-time processing and offers features like data retention for up to 365 days, enabling consumers to reprocess data if needed. Amazon SNS with fan-out to SQS queues can work, but it's generally more expensive for high-volume, real-time streaming data compared to Kinesis Data Streams, especially when considering the operational overhead of managing numerous SQS queues for each consumer. Using SQS FIFO queues (Option B) adds ordering guarantees, which are not explicitly required by the question and would further increase cost and complexity without providing the same real-time streaming capabilities as Kinesis Data Streams. Amazon Kinesis Firehose (Option C) is primarily for delivering streaming data to destinations like S3, Redshift, or Splunk, not for concurrent processing by multiple custom applications.