Tech Tips: June 2021

Summary

This post will demonstrate the usage of Google Cloud's serverless deployment pipeline - Cloud Build. The use case for this will be a fairly simple Python app that exposes a REST interface via Flask + NLTK for tokenization of text.

Overall Architecture

The diagram below depicts the Cloud Build pipeline.

Python Application Organization

Cloud Build Steps

Cloud Build is orchestrated from a cloudbuild.yaml file. Example code below with associated diagram.

steps:
  #Unit Test
  - name: python
    entrypoint: /bin/sh
    args: ["-c", 
     "pip install -r requirements.txt &&\ 
     python -c \"import nltk; nltk.download('popular', download_dir='/home/nltk_data')\" &&\
     export NLTK_DATA=/home/nltk_data &&\ 
     python -m unittest"] 
  
  #Docker Build
  - name: 'gcr.io/cloud-builders/docker'
    args: ['build', '-t', 
            'us-central1-docker.pkg.dev/$PROJECT_ID/$_REPO_NAME/cleaner', '.']
  
  #Docker push to Google Artifact Registry
  - name: 'gcr.io/cloud-builders/docker'
    args: ['push',  'us-central1-docker.pkg.dev/$PROJECT_ID/$_REPO_NAME/cleaner']
  
  #Deploy to Cloud Run
  - name: google/cloud-sdk
    args: ['gcloud', 'run', 'deploy', 'cleaner', 
           '--image=us-central1-docker.pkg.dev/$PROJECT_ID/$_REPO_NAME/cleaner', 
           '--region', 'us-central1', '--platform', 'managed', 
           '--allow-unauthenticated']