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Google Cloud Run Deployment Guide

Deploy VerityNgn API to Google Cloud Run for production use.

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Prerequisites

  • Google Cloud Project with billing enabled
  • gcloud CLI installed and configured
  • Docker installed locally
  • Service account with Vertex AI and Cloud Run permissions

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Quick Deploy

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1. Set Project

gcloud config set project YOUR_PROJECT_ID
export PROJECT_ID=$(gcloud config get-value project)
export REGION="us-central1"

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2. Enable APIs

gcloud services enable \
  run.googleapis.com \
  artifactregistry.googleapis.com \
  aiplatform.googleapis.com

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3. Create Artifact Registry

gcloud artifacts repositories create verityngn \
  --repository-format=docker \
  --location=$REGION

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4. Build and Push Image

# Build image
docker build -f Dockerfile.api -t verityngn-api .

# Tag for Artifact Registry
docker tag verityngn-api \
  $REGION-docker.pkg.dev/$PROJECT_ID/verityngn/api:latest

# Push
docker push $REGION-docker.pkg.dev/$PROJECT_ID/verityngn/api:latest

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5. Deploy to Cloud Run

gcloud run deploy verityngn-api \
  --image=$REGION-docker.pkg.dev/$PROJECT_ID/verityngn/api:latest \
  --platform=managed \
  --region=$REGION \
  --allow-unauthenticated \
  --memory=4Gi \
  --cpu=2 \
  --timeout=3600 \
  --set-env-vars="DEPLOYMENT_MODE=production,STORAGE_BACKEND=gcs,GCS_BUCKET_NAME=your-bucket" \
  --set-secrets="GOOGLE_SEARCH_API_KEY=google_search_key:latest,CSE_ID=cse_id:latest"

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Configuration

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Environment Variables

Set in Cloud Run:
  • DEPLOYMENT_MODE=production
  • STORAGE_BACKEND=gcs
  • GCS_BUCKET_NAME=your-bucket-name
  • VERTEX_MODEL_NAME=gemini-2.0-flash-exp

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Secrets

Store API keys in Google Secret Manager: 
# Create secrets
echo -n "your-api-key" | gcloud secrets create google_search_key --data-file=-
echo -n "your-cse-id" | gcloud secrets create cse_id --data-file=-

# Grant access to Cloud Run service account
gcloud secrets add-iam-policy-binding google_search_key \
  --member="serviceAccount:YOUR_SERVICE_ACCOUNT" \
  --role="roles/secretmanager.secretAccessor"

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Streamlit UI Deployment

Deploy to Streamlit Cloud:
  1. Push code to GitHub
  2. Go to share.streamlit.io
  3. Connect repository
  4. Set app path: ui/streamlit_app.py
  5. Add secrets in .streamlit/secrets.toml: 
    VERITYNGN_API_URL = "https://your-service.run.app"

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Monitoring

View logs: 
gcloud run services logs read verityngn-api --region=$REGION

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Cost Estimation

  • Cloud Run: 0.00002400/vCPU−second,0.00002400/vCPU-second, 0.00000250/GiB-second
  • Vertex AI: ~$0.25 per video
  • Storage: ~$0.02/GB/month
  • Expected: $10-50/month for light usage
See DEPLOYMENT_LOCAL.md for local testing.