Automating Stream to YouTube Workflow with AWS | chill sunday morning coding - Episode 193
2In this video, I work on enhancing my automation tool designed to streamline the process of taking livestream content and transforming it into ready-to-upload YouTube videos. This project has been an ongoing endeavor for over a year, with the latest focus on a major rewrite leveraging AWS to improve scalability and functionality.
The tool automates tasks such as extracting data from livestreams, generating titles and descriptions using AI, and organizing videos into customized episodes for YouTube. I discuss challenges like data storage, workflow logic improvements, and how to design a system capable of creating professional video edits seamlessly within a single application—eliminating the need for external video editors.
Topics covered include:
Fixing bugs causing errors in the video ingestion pipeline
Rearranging workflow steps involving DynamoDB and parsing video data
Exploring Twitch’s video producer and segmenting features
Discussing storage costs and scalability of the system
Using AI features for auto-summarization and content curation
This tool aims to provide a one-stop platform that brings editing, management, and publishing together, offering a creative studio for content creators directly integrated with streaming workflows.
🔗 Check out my Twitch channel for more streams: https://www.twitch.tv/saebyn
GitHub: https://github.com/saebyn
Discord: https://discord.gg/N7xfy7PyHs