Designing a Layered YouTube Analytics Pipeline with AWS Bedrock (Architecture Overview

Most analytics pipelines measure what happened. I wanted to measure why it matters, using LLM-powered semantic enrichment to understand content quality, not just view counts. Here's the architecture that makes it possible: a medallion-style YouTube analytics pipeline with AWS Bedrock for semantic intelligence. A layered approach: EventBridge orchestration → AWS Glue processing → Bedrock semantic enrichment → Athena analytics Key Design Decisions Medallion Architecture (Bronze → Silver → Gold) Bronze: Raw YouTube API snapshots (append-only historical record) Silver: Cleaned, normalized data with growth metrics Gold: Behavioral metrics + LLM-enriched semantic attributes Semantic Enrichment as a Separate Layer The critical choice: enrich in Gold, not Silver. Why? Content attributes (educational depth, emotional tone, clickbait score) are static. View counts change daily. Enriching in Gold means: Enrich once, not on every daily run 30x cost savings on Bedrock API calls Can backfill semanti