Kubeflow

Kubeflow simplifies the deployment of machine learning workflows in Kubernetes environments. It provides tools for building, training, and deploying ML models at scale.

Key Features

• Native integration with Kubernetes
• Supports multiple ML frameworks
• Customizable pipelines for ML workflows
• User-friendly UI for managing experiments

Pros

• Cost-effective: Free and open-source
• Highly scalable for large workloads
• Active community and ongoing support
• Flexible architecture for diverse ML needs

Cons

• Steeper learning curve for beginners
• Limited native features compared to commercial tools
• Requires Kubernetes knowledge for setup
• Potential performance issues with complex workflows