Vertex AI TensorBoard custom training with custom container: Notebook
Stay organized with collections
Save and categorize content based on your preferences.
In this tutorial, you learn how to create a custom training job using custom
containers, and monitor your training process on Vertex AI TensorBoard
in near real time.
Notebook: Create custom training jobs using custom containers
This tutorial uses the following Google Cloud ML services and resources:
Vertex AI training
Vertex AI TensorBoard
The steps performed include:
Create a Docker repository and config.
Create a custom container image with your customized training code.
Set up a service account and Cloud Storage buckets.
Create and launch your custom training job with your custom container.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Hard to understand","hardToUnderstand","thumb-down"],["Incorrect information or sample code","incorrectInformationOrSampleCode","thumb-down"],["Missing the information/samples I need","missingTheInformationSamplesINeed","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2025-08-25 UTC."],[],[],null,["# Vertex AI TensorBoard custom training with custom container: Notebook\n\nIn this tutorial, you learn how to create a custom training job using custom\ncontainers, and monitor your training process on Vertex AI TensorBoard\nin near real time.\n\nNotebook: Create custom training jobs using custom containers\n-------------------------------------------------------------\n\n| To see an example of tensorboard custom training with custom container,\n| run the \"Vertex AI TensorBoard custom training with custom container\" notebook in one of the following\n| environments:\n|\n| [Open in Colab](https://colab.research.google.com/github/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/official/tensorboard/tensorboard_custom_training_with_custom_container.ipynb)\n|\n|\n| \\|\n|\n| [Open in Colab Enterprise](https://console.cloud.google.com/vertex-ai/colab/import/https%3A%2F%2Fraw.githubusercontent.com%2FGoogleCloudPlatform%2Fvertex-ai-samples%2Fmain%2Fnotebooks%2Fofficial%2Ftensorboard%2Ftensorboard_custom_training_with_custom_container.ipynb)\n|\n|\n| \\|\n|\n| [Open\n| in Vertex AI Workbench](https://console.cloud.google.com/vertex-ai/workbench/deploy-notebook?download_url=https%3A%2F%2Fraw.githubusercontent.com%2FGoogleCloudPlatform%2Fvertex-ai-samples%2Fmain%2Fnotebooks%2Fofficial%2Ftensorboard%2Ftensorboard_custom_training_with_custom_container.ipynb)\n|\n|\n| \\|\n|\n| [View on GitHub](https://github.com/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/official/tensorboard/tensorboard_custom_training_with_custom_container.ipynb)\n\nThis tutorial uses the following Google Cloud ML services and resources:\n\n- Vertex AI training\n- Vertex AI TensorBoard\n\nThe steps performed include:\n\n- Create a Docker repository and config.\n- Create a custom container image with your customized training code.\n- Set up a service account and Cloud Storage buckets.\n- Create and launch your custom training job with your custom container.\n\nRelevant content\n----------------\n\n- [Vertex AI TensorBoard](/vertex-ai/docs/experiments/tensorboard-introduction)\n- [Custom training](/vertex-ai/docs/training/overview)"]]