Using Gcp Cloudbuild With Notebooks

Introduction

In this guide, we will demonstrate how to use Google Cloud Build to build and deploy Jupyter Notebooks. Google Cloud Build is a service that executes your builds on Google Cloud infrastructure. It can import source code from various repositories or cloud storage spaces, execute a build to your specifications, and produce artifacts such as Docker containers or JavaScript bundles.

Step-by-Step Explanation

Step 1: Set Up Google Cloud Project

1. Go to the Google Cloud Console.
2. Create a new project or select an existing project.
3. Enable the Cloud Build API for your project.

Step 2: Create a Cloud Build Configuration File

1. Create a cloudbuild.yaml file in your project directory.
2. Define the build steps in the cloudbuild.yaml file. For example, you can define steps to build a Docker image for your Jupyter Notebook.

Step 3: Create a Dockerfile for Jupyter Notebook

1. Create a Dockerfile in your project directory.
2. Define the Docker image for your Jupyter Notebook. For example, you can use the jupyter/base-notebook image as a base image.

Step 4: Trigger the Build

1. Use the gcloud command-line tool to trigger the build.
2. Run the following command to start the build: gcloud builds submit --config cloudbuild.yaml .

Key Points

• Google Cloud Build: A service for executing builds on Google Cloud infrastructure.
• Cloud Build Configuration: Requires a cloudbuild.yaml file to define build steps.
• Dockerfile: Used to define the Docker image for Jupyter Notebooks.
• Build Trigger: Initiated using the gcloud command-line tool.

Summary

In this guide, we have shown how to use Google Cloud Build to build and deploy Jupyter Notebooks. We covered setting up a Google Cloud project, creating a Cloud Build configuration file, creating a Dockerfile for Jupyter Notebook, and triggering the build using the gcloud command-line tool. By following these steps, you can automate the build and deployment of your Jupyter Notebooks using Google Cloud Build.

Using Pulumi with Google Cloud Build and Notebooks allows for efficient infrastructure management and automation. This integration simplifies the process of maintaining and scaling Jupyter Notebooks environments, enhancing productivity and ensuring consistency across deployments. Embracing these tools can significantly streamline your workflow and improve the reliability of your deployment processes.

Full Code Example

import * as pulumi from "@pulumi/pulumi";
import * as gcp from "@pulumi/gcp";

// Create a Google Cloud Build Trigger
const buildTrigger = new gcp.cloudbuild.Trigger("jupyter-notebook-build-trigger", {
    filename: "cloudbuild.yaml",
    includedFiles: ["**/*"],
    substitutions: {
        "_NOTEBOOK_IMAGE": "gcr.io/my-project/jupyter-notebook:latest",
    },
    triggerTemplate: {
        projectId: pulumi.getProject(),
        repoName: "my-repo",
        branchName: "^main$",
    },
});

// Create a Google Cloud Notebooks Instance
const notebookInstance = new gcp.notebooks.Instance("jupyter-notebook-instance", {
    machineType: "n1-standard-4",
    installGpuDriver: false,
    customGpuDriverPath: "",
    bootDiskType: "PD_STANDARD",
    bootDiskSizeGb: 100,
    dataDiskType: "PD_STANDARD",
    dataDiskSizeGb: 100,
    noRemoveDataDisk: false,
    location: "us-central1-a",
    vmImage: {
        project: "deeplearning-platform-release",
        imageFamily: "tf-latest-cpu",
    },
});

// Export the URLs of the build trigger and the notebook instance
export const buildTriggerUrl = pulumi.interpolate`https://console.cloud.google.com/cloud-build/triggers/edit/${buildTrigger.id}?project=${pulumi.getProject()}`;
export const notebookInstanceUrl = pulumi.interpolate`https://console.cloud.google.com/ai/notebooks/instances/details/${notebookInstance.id}?project=${pulumi.getProject()}`;