What does this AWS Solution Implementation do?

Amazon Web Services (AWS) offers highly scalable, elastic, and secure cloud services that help customers more easily ingest, store, process, deliver, and manage content in the cloud. Moving your digital asset management to the cloud enables you to take advantage of the latest innovations in asset management and supply chain applications. However, it can be a challenging and slow process to migrate your existing video archives to the cloud.

To help streamline and automate the migration process, AWS offers the Media2Cloud solution. This solution sets up a serverless end-to-end ingest workflow to move your video assets and associated metadata to the cloud. During the migration, the solution analyzes and extracts valuable metadata from your video and images using Amazon Rekognition, Amazon Transcribe, and Amazon Comprehend. Media2Cloud also includes a simple web interface that enables you to immediately start ingesting and analyzing your content to enrich its value.

AWS Solution Implementation overview

This solution enables customers to quickly and seamlessly extract key details from their media files in their AWS accounts without machine learning expertise. The solution also includes a web-based user interface that customers can use to upload and search their image, audio, and video files.

Media2Cloud | Architecture Diagram
 Click to enlarge

Media2Cloud solution architecture

The AWS CloudFormation template deploys three workflows: one that ingests source videos and images, one that analyzes and extracts machine learning metadata from your content, and one that creates and manages labeling jobs.

When you upload a video or image to the ingest Amazon Simple Storage Service (Amazon S3) bucket, the ingest workflow creates a standardized proxy file and thumbnails for analysis. The analysis workflow analyzes the videos and images and extracts metadata using AWS-native AI services. The labeling workflow uses Amazon SageMaker Ground Truth to create labeling jobs for your workforce that are used to tag faces to your face collection.

The ingest Amazon S3 bucket has an Amazon S3 lifecycle policy that allows the solution to move uploaded videos and images to Amazon S3 Glacier for archiving.

The ingest workflow leverages AWS StepFunctions and AWS Lambda to orchestrate the ingest workflow and trigger AWS Elemental MediaConvert to create standardized proxy files and thumbnails of the uploaded videos and images for analysis. Proxy files are stored in a proxy Amazon S3 bucket, and media information is stored in Amazon DynamoDB. When video processing is completed, Amazon Simple Notification Service (Amazon SNS) sends notifications to subscribers.

An Amazon API Gateway RESTful API is used for searching results stored in an Amazon Elasticsearch Service (Amazon ES) cluster, and AWS IoT Core is used as a publish/subscribe message broker to periodically update workflow progress to connected web clients.

The solution also deploys a simple web interface that makes it easy to upload, browse, search video and image files, extract metadata, and create and manage your labeling workforce. The web interface leverages Amazon Cognito for user authentication and is powered by web assets hosted in an Amazon S3 bucket. Amazon CloudFront is used to provide public access to the solution’s website bucket contents.


Version 2.0.1
Last updated: 12/2019
Author: AWS

Estimated deployment time: 25 min

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Media2Cloud reference implementation

Leverage the Media2Cloud solution out of-the-box, or as a reference implementation for building a serverless framework to accelerate the setup and configuration of a content ingest process.

User interface

The solution creates a simple web interface that makes it easy to upload, browse, and search video and image files and extracted metadata.
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