Vertex AI TensorBoard with Vertex AI Pipelines: Notebook

In this tutorial, you'll learn how to create a training pipeline using the KFP SDK, execute the pipeline in Vertex AI Pipelines, and monitor your training process on Vertex AI TensorBoard in near real time.

To see an example of tensorboard integration with pipelines, run the "Vertex AI TensorBoard  integration with  Vertex AI Pipelines" Jupyter notebook in one of the following environments:

Open in Colab | Open in Colab Enterprise | Open in Vertex AI Workbench user-managed notebooks | View on GitHub

This tutorial uses the following Google Cloud ML services and resources:

• Vertex AI training
• Vertex AI TensorBoard
• Vertex AI Pipelines

The steps performed include:

• Setup a service account and Cloud Storage buckets.
• Construct a Kubeflow Pipelines (KPT) with your custom training code.
• Compile and execute the KFP pipeline in Vertex AI Pipelines with Vertex AI TensorBoard enabled for near real time monitoring.

Relevant content

• Use Vertex AI TensorBoardwith Vertex AI Pipelines