Kubeflow

Kubeflow simplifies deploying machine learning workflows on Kubernetes. It offers tools for orchestration, serving, and monitoring models seamlessly.

Key Features

• Supports end-to-end ML workflows.
• Integrates with various Kubernetes services.
• Facilitates model serving and management.
• Offers visualization tools for pipeline tracking.
• Compatible with popular ML frameworks.

Pros

• Free and open-source.
• Strong community support.
• Highly scalable for large projects.
• Flexible architecture for customization.

Cons

• Steep learning curve for beginners.
• Requires Kubernetes expertise.
• Limited out-of-the-box features.
• Can be complex to set up and maintain.