Observability in Production: Monitoring Data Drift with WhyLabs and Valohai

The text discusses the importance of observability in production for machine learning models. It highlights that even after a model is deployed, continuous monitoring and evaluation are necessary to prevent issues like data drift. The article mentions tools such as WhyLabs and Valohai that can help detect data drift and improve AI observability. It also refers to real-world examples of companies facing consequences due to faulty predictions from their machine learning models.