Mastering Advanced Pipeline Design: Conditional Execution and Loops in Kubeflow Kubeflow Pipelines provide a powerful platform for building, deploying, and managing machine learning workflows. To create more complex and dynamic pipelines, you may need to use conditional execution and loops. In this tutorial, we will guide you through the process of implementing conditional execution and loops in Kubeflow Pipelines using Python. Step 1: Define a Conditional Execution Function To demonstrate conditional execution in Kubeflow Pipelines, we will create a simple…
Containerizing Your Code: Docker and Kubeflow Pipelines
Containerizing Your Code: Docker and Kubeflow Pipelines Kubeflow Pipelines allows you to build, deploy, and manage end-to-end machine learning workflows. In order to use custom code in your pipeline, you need to containerize it using Docker. This ensures that your code can be easily deployed, scaled, and managed by Kubernetes, which is the underlying infrastructure for Kubeflow. In this tutorial, we will guide you through containerizing your Python code using Docker and integrating it into a Kubeflow Pipeline. Prerequisites Docker…