Kubeflow vs MLflow - Which MLOps tool should you use

MLOps has quickly become one of the most important components of data science, with the market expected to grow by almost $4 billion by 2025. It is already being leveraged heavily with companies like Amazon, Google, Microsoft, IBM, H2O, Domino, DataRobot and Grid.ai using MLOps for pipeline automation, monitoring, lifecycle management and governance. More and more MLOps tools are being developed to address different parts of the workflow, with two dominating the space, Kubeflow and MLflow. Given their open-sourced nature, Kubeflow and MLflow are both chosen by leading tech companies. However, their capabilities and offerings are quite different when compared. For example, while Kubeflow is pipeline focused, MLflow is experimentation based.