Jorrick Stempher breaks down the 5-component architecture his team built for predictive Kubernetes scaling.

He walks through the complete data pipeline: Prometheus collecting cluster metrics, a NestJS adapter that validates and cleans data before storing it in PostgreSQL, the Prophet machine learning model generating 60-minute CPU load predictions, an Index Calculation Component (ICC) that converts predictions into scaling decisions using a custom abstract metric, and Grafana for real-time visualization comparing predictions against actual performance.

Watch the full episode: https://ku.bz/clbDWqPYp