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Hi,
If you have many videos which you would like to process through Rekognition Video, we recommend an architecture similar to the one describe in https://github.com/aws-samples/amazon-textract-serverless-large-scale-document-processing/blob/master/README.md, specifically the async section of the architecture.
In this architecture, you submit messages to a SQS queue and then a lambda schedules jobs to Rekognition Video as existing jobs are completed. You can re-use the same code as in the above github link, just change calls from Textract to Rekognition, and it should work.
As of now, there is no way to understand number of jobs in progress, so we recommend the above architecture for large scale jobs processing.
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