Automated Video/Audio Processing Tutorial (Apache Airflow)

In this tutorial, we explore the world of Apache Airflow by orchestrating a media processing pipeline using Google Cloud Composer. Specifically, we'll guide you through an end-to-end workflow for extracting audio from video files, transcribing the audio using Google Cloud Speech-to-Text, and saving the transcript to cloud storage.

Key takeaways:
1. Learn how to set up and manage a serverless Cloud Composer environment on Google Kubernetes Engine Autopilot.
2. Build a DAG to extract audio from video files using ffmpeg and the Kubernetes Pod Operator.
3. Create a custom operator for long audio transcription jobs with Google Cloud Speech-to-Text.
4. Use Python operators to clean up and upload the transcript to Google Cloud Storage.
5. Gain insights into managing Kubernetes permissions and RBAC to ensure smooth execution of your DAGs.

Modeling Tool: https://softwaresim.com

Demonstration Code: https://github.com/nodematiclabs/media-processing-airflow

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0:00 Conceptual Overview
1:02 Cloud Composer Setup
2:54 Code Review (Part 1)
6:37 Cloud Storage Bucket Creation
7:13 Code Review (Part 2)
14:01 DAG Instantiation