Features of Kubeflow on GCP

Reasons to use Kubeflow on Google Cloud Platform (GCP)

Running Kubeflow on GCP has the following benefits:

  • The Cloud Connector to declaratively manage all non-Kubernetes resources (including the GKE cluster).
  • You can take advantage of GKE’s Cluster Autoscaler to automatically resize the number of nodes in a node pool in your cluster depending on the workload demands.
  • Cloud Identity-Aware Proxy (Cloud IAP) makes it easy to securely connect to Jupyter and other web apps running as part of Kubeflow.
  • Stackdriver provides persistent logs to aid in debugging and troubleshooting.
  • You can use GPUs and Cloud TPU to accelerate your workload.

Next steps