YouTube Search is about understanding intent across billions of queries while managing complex metadata at scale and delivering real-time analytics.
This session bridges my experience as a broadcast engineer at YouTube Space LA to the developer and open source community. We'll explore practical lessons from YouTube's search infrastructure and show how to maximize these challenges - from ambiguous queries to recommendation systems.
You'll learn:
1) Observability at Scale: What YouTube’s metadata means for your AIOps and observability stack
2) Platform Engineering for Search: Building developer-friendly search infrastructure that your teams will actually want to use
3) Real-time Analytics: Building pipelines that power recommendation engines that power both dashboards and ML-driven insights
As developer advocates, we know that effective discovery isn't just about finding content - it's about connecting developers with the knowledge they need to grow so that the next generation can build on what we've learned.