Cake for
MLOps

Overview

Getting a model to work in a notebook is one thing. Making it work in production—securely, scalably, and repeatably—is the real challenge. MLOps is the missing layer between experiments and real-world value, but most existing stacks are either rigid, proprietary, or overly complex.

Cake gives you a composable, cloud-agnostic MLOps foundation built from open-source tools. Track experiments, manage model versions, deploy with autoscaling, and monitor performance, all within a system that prioritizes flexibility, speed, and control.

Every component is open-source, swappable, and orchestrated with Cake-native workflows, so you’re never locked into a single vendor or architecture. You get the benefits of modularity without sacrificing enterprise-grade observability or operational rigor.

Key benefits

• Accelerate deployment cycles: Move from experimentation to production without duplicating infrastructure.
  
  

• Build a modular stack: Choose the best tools for each stage of the ML lifecycle.
  
  

• Monitor everything: Detect drift, debug failures, and track model performance in real time.