In this episode we're hosting Simon Aronsson, Senior Engineering Manager for Canonical Observability Stack.
Machine learning operations (MLOps) is a new practice that ensures ML workflow automation in a scalable and efficient manner. But how do you make MLOps observable? How can you better understand how your product-grade AI initiative and its infrastructure are performing?
This is where observability comes in.
Learn more about our solutions here: https://ubuntu.com/ai
In this episode we're hosting Simon Aronsson, Senior Engineering Manager for Canonical Observability Stack.
Machine learning operations (MLOps) is a new practice that ensures ML workflow automation in a scalable and efficient manner. But how do you make MLOps observable? How can you better understand how your product-grade AI initiative and its infrastructure are performing?
This is where observability comes in.
Learn more about our solutions here: https://ubuntu.com/ai