Which solution will meet these requirements MOST cost-effectively?
Use Amazon Kinesis Video Streams to ingest, index, and store the data. Use the built-in integration with Amazon Rekognition for viewing by the security team.
Use Amazon Kinesis Video Streams to ingest, index, and store the data. Use the built-in HTTP live streaming (HLS) capability for viewing by the security team.
Use Amazon Rekognition Video and the GStreamer plugin to ingest the data for viewing by the security team. Use Amazon Kinesis Data Streams to index and store the data.
Use Amazon Kinesis Data Firehose to ingest, index, and store the data. Use the built-in HTTP live streaming (HLS) capability for viewing by the security team.
Explanations:
Amazon Kinesis Video Streams is designed for streaming video, but using Amazon Rekognition is not the most cost-effective way to provide real-time access for the security team. Rekognition is more suitable for analyzing video content, not simply viewing it.
Amazon Kinesis Video Streams provides video ingestion and storage. The built-in HTTP Live Streaming (HLS) capability allows the security team to view the video in real-time. This solution is cost-effective for both ingestion and viewing.
Amazon Rekognition Video is not necessary for simply viewing the data in real-time. The GStreamer plugin is used for video processing, but Kinesis Data Streams is more suited for indexing and storage, not video streaming. This solution is overly complex.
Amazon Kinesis Data Firehose is primarily used for data delivery (not video ingestion). It cannot efficiently handle video streaming. HLS is useful for viewing, but Kinesis Data Streams (option B) is better suited for this use case.
I evaluate that the answer is:
Use Amazon Kinesis Video Streams to ingest, index, and store the data. Use the built-in HTTP live streaming (HLS) capability for viewing by the security team.