A media company has a 30-TB repository of digital news videos. These videos are stored on tape in an on-premises tape library and referenced by a Media Asset Management (MAM) system. The company wants to enrich the metadata for these videos in an automated fashion and put them into a searchable catalog by using a MAM feature. The company must be able to search based on information in the video, such as objects, scenery items, or people’s faces. A catalog is available that contains faces of people who have appeared in the videos that include an image of each person. The company would like to migrate these videos to AWS.
The company has a high-speed AWS Direct Connect connection with AWS and would like to move the MAM solution video content directly from its current file system.
How can these requirements be met by using the LEAST amount of ongoing management overhead and causing MINIMAL disruption to the existing system?
A. Set up an AWS Storage Gateway, file gateway appliance on-premises. Use the MAM solution to extract the videos from the current archive and push them into the file gateway. Use the catalog of faces to build a collection in Amazon Rekognition. Build an AWS Lambda function that invokes the Rekognition Javascript SDK to have Rekognition pull the video from the Amazon S3 files backing the file gateway, retrieve the required metadata, and push the metadata into the MAM solution.
B. Set up an AWS Storage Gateway, tape gateway appliance on-premises. Use the MAM solution to extract the videos from the current archive and push them into the tape gateway. Use the catalog of faces to build a collection in Amazon Rekognition. Build an AWS Lambda function that invokes the Rekognition Javascript SDK to have Amazon Rekognition process the video in the tape gateway, retrieve the required metadata, and push the metadata into the MAM solution.
C. Configure a video ingestion stream by using Amazon Kinesis Video Streams. Use the catalog of faces to build a collection in Amazon Rekognition. Stream the videos from the MAM solution into Kinesis Video Streams. Configure Amazon Rekognition to process the streamed videos. Then, use a stream consumer to retrieve the required metadata, and push the metadata into the MAM solution. Configure the stream to store the videos in Amazon S3.
D. Set up an Amazon EC2 instance that runs the OpenCV libraries. Copy the videos, images, and face catalog from the on-premises library into an Amazon EBS volume mounted on this EC2 instance. Process the videos to retrieve the required metadata, and push the metadata into the MAM solution, while also copying the video files to an Amazon S3 bucket.
The company has a high-speed AWS Direct Connect connection with AWS and would like to move the MAM solution video content directly from its current file system.
How can these requirements be met by using the LEAST amount of ongoing management overhead and causing MINIMAL disruption to the existing system?
A. Set up an AWS Storage Gateway, file gateway appliance on-premises. Use the MAM solution to extract the videos from the current archive and push them into the file gateway. Use the catalog of faces to build a collection in Amazon Rekognition. Build an AWS Lambda function that invokes the Rekognition Javascript SDK to have Rekognition pull the video from the Amazon S3 files backing the file gateway, retrieve the required metadata, and push the metadata into the MAM solution.
B. Set up an AWS Storage Gateway, tape gateway appliance on-premises. Use the MAM solution to extract the videos from the current archive and push them into the tape gateway. Use the catalog of faces to build a collection in Amazon Rekognition. Build an AWS Lambda function that invokes the Rekognition Javascript SDK to have Amazon Rekognition process the video in the tape gateway, retrieve the required metadata, and push the metadata into the MAM solution.
C. Configure a video ingestion stream by using Amazon Kinesis Video Streams. Use the catalog of faces to build a collection in Amazon Rekognition. Stream the videos from the MAM solution into Kinesis Video Streams. Configure Amazon Rekognition to process the streamed videos. Then, use a stream consumer to retrieve the required metadata, and push the metadata into the MAM solution. Configure the stream to store the videos in Amazon S3.
D. Set up an Amazon EC2 instance that runs the OpenCV libraries. Copy the videos, images, and face catalog from the on-premises library into an Amazon EBS volume mounted on this EC2 instance. Process the videos to retrieve the required metadata, and push the metadata into the MAM solution, while also copying the video files to an Amazon S3 bucket.