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Persist Workflow State with DynamoDB
The beginnings of a media processing pipeline are in development! An existing Lambda function processes videos uploaded to a source S3 bucket, but a place to store metadata about the processing pipeline needs to be created. In this lab, you will use DynamoDB to create a serverless table to store metadata about objects in the pipeline, then update the provided Node.js Lambda function to create a table item storing information about the object, job ID, and transcoding status. You will then test the pipeline to ensure function.
Lab Info
Table of Contents
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Challenge
Expand a partially-created video pipeline
Review the existing pipeline infrastructure and create a plan for extending it to include metadata support.
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Challenge
Create a DynamoDB table to store metadata about processing jobs
Learn to create a DynamoDB table with the appropriate sort key and Global Secondary Index to store data about each video file and related processing jobs.
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Challenge
Update an existing Lambda function with new functionality for writing to database tables
Review and update a Node.js-based Lambda function to add additional functionality by updating the database table with the desired metadata fields.
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Challenge
Test the pipeline with the provided assets
Use the provided mp4 file to test the updated pipeline, ensuring the Lambda function not just triggers an Elemental MediaConvert job that runs successfully, but also updates the newly-created table with the necessary metadata.
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