How to Create a Cloud Build to Allow Docker to Download Python Packages from Artifact Registry

Google Cloud's Artifact Registry is a powerful tool for managing your application's dependencies. This guide demonstrates how to create a Cloud Build pipeline to enable Docker to access Python packages stored in Artifact Registry. By following these steps, you can securely manage dependencies and streamline deployments.

Prerequisites

1. 
   Google Cloud Project: Ensure you have a GCP project set up.


2. 
   Artifact Registry: A Python repository should already be configured in the Artifact Registry.


3. 
   Cloud Build: Enable the Cloud Build API for your project.


4. 
   Authentication: Configure service account permissions to access the Artifact Registry.

Steps to Configure Cloud Build

1. Generate an Artifact Registry Token

Use gcloud auth to generate an access token that will allow the Docker build process to authenticate with the Artifact Registry. Here's how you can do this:

steps:

  # Generate Artifact Registry token

  - name: 'gcr.io/google.com/cloudsdktool/cloud-sdk'

    entrypoint: bash

    args:

      - '-c'

      - |

        art=$(gcloud auth print-access-token)

        echo "$art" > /workspace/artifact_registry_token

        echo "$art"

2. Use the Token in Docker Build

Once the token is generated, it can be passed to the docker build process as a build argument. Here's how:

  - name: gcr.io/cloud-builders/docker

    id: Build

    env:

      - 'btf=/workspace/artifact_registry_token'

    entrypoint: bash

    args:

      - '-c'

      - |

        docker build \

          --build-arg ARTIFACT_REGISTRY_TOKEN=$(cat $btf) \

          --build-arg PROJECT_ID=$PROJECT_ID \

          -t test-image:latest \

          -f Dockerfile .

3. Create the Dockerfile

The Dockerfile is configured to use the token to download Python packages from Artifact Registry:

# syntax=docker/dockerfile:1



FROM python:3.11-slim



ARG ARTIFACT_REGISTRY_TOKEN

ARG PROJECT_ID



# Keeps Python from buffering stdout and stderr

ENV PYTHONUNBUFFERED=1



WORKDIR /app



RUN pip install --no-cache-dir -r requirements.txt



COPY . .



# Install dependencies using the token

RUN pip install \

    --index-url https://pypi.org/simple \

    --extra-index-url https://oauth2accesstoken:${ARTIFACT_REGISTRY_TOKEN}@us-central1-python.pkg.dev/${PROJECT_ID}/python-packages/simple/ \

    "your-package-name==your-package-version"



# Expose the application port

EXPOSE 8080



# Command to run the application

CMD ["uvicorn", "main:app", "--port=8080", "--host=0.0.0.0"]

4. Add Build Config Options

Finally, define other configurations such as machine type, logging, and substitutions:

options:

  machineType: E2_HIGHCPU_8

  substitutionOption: ALLOW_LOOSE

  logging: CLOUD_LOGGING_ONLY

substitutions:

  _PACKAGE: your-package-name==your-package-version

  _REPOSITORY: python-packages

  _LOCATION: us-central1

  _PROJECT_ID: your-project-id

Tags and Metadata

To organize your builds better, include meaningful tags:

tags:

  - gcp-cloud-build

  - artifact-registry

  - docker-python-packages

Summary

This setup ensures that your Docker builds in Cloud Build can securely pull Python dependencies from your Artifact Registry using an access token. Adjust the provided configuration to your project-specific details, such as package names, repository URLs, and deployment targets.

Implementing this pipeline will improve security and make dependency management seamless for your projects.