Towards Observability for ML Pipelines // Shreya Shankar // MLOps Coffee Sessions #75

MLOps Coffee Sessions #75 with Shreya Shankar, Towards Observability for ML Pipelines.



// Abstract

Achieving observability in ML pipelines is a mess right now. We are tracking thousands of means, percentiles, and KL divergences of features and outputs in a haphazard attempt to figure out when and how to retrain models.



In this session, we break down current unsuccessful approaches and discuss the path towards effectively maintaining ML models in production. Along the way, we introduce mltrace -- a preliminary …

coffee mlops ml pipelines observability pipelines