Kubeflow: An End-to-end Machine Learning Lab

As we described earlier in this chapter, TensorFlow was designed to utilize distributed resources for training. To leverage this capability, we will use the Kubeflow projects. Built on top of Kubernetes, Kubeflow has several components that are useful in the end-to-end process of managing machine learning applications. To install Kubeflow, we need to have an existing Kubernetes control plane instance and use kubectl to launch Kubeflow’s various components. The steps for setup differ slightly depending on whether we are using a local instance or one of the major cloud providers.