Cloud Run Deployment

This directory contains deployment configurations for running the Accessible Video Platform on Google Cloud Run.

Files

cloudbuild.yaml - Cloud Build configuration for CI/CD
api-service.yaml - Cloud Run service definition for API
worker-service.yaml - Cloud Run service definition for Celery workers
main.tf - Terraform infrastructure as code
terraform.tfvars.example - Example Terraform variables
deploy.sh - Manual deployment script
README.md - This file

Prerequisites

Google Cloud Project with billing enabled
Required APIs enabled (script will enable them):
- Cloud Build API
- Cloud Run API
- Container Registry API
- Secret Manager API
- Cloud Trace API
- Cloud Monitoring API
- Translate API
- Text-to-Speech API
- Cloud Storage API
- AI Platform API
Secrets created in Secret Manager:
- mongodb-url - MongoDB Atlas connection string
- redis-url - Redis connection string (Cloud Memorystore)
- jwt-secret - JWT signing secret
- jwt-refresh-secret - JWT refresh token secret
- gemini-api-key - Google Gemini API key
- sendgrid-api-key - SendGrid API key for emails
- elevenlabs-api-key - ElevenLabs API key for TTS
- sentry-dsn - Sentry error tracking DSN

Deployment Options

Option 1: Terraform (Recommended)

# Initialize Terraform
cd infra/cloud-run
terraform init

# Copy and configure variables
cp terraform.tfvars.example terraform.tfvars
# Edit terraform.tfvars with your project details

# Plan deployment
terraform plan

# Deploy infrastructure
terraform apply

Option 2: Manual Script

# Set environment variables
export PROJECT_ID="your-gcp-project-id"
export REGION="us-central1"

# Run deployment script
./infra/cloud-run/deploy.sh

Option 3: Cloud Build Trigger

Set up a Cloud Build trigger connected to your Git repository that uses cloudbuild.yaml for automatic deployments on code changes.

Local Development

Use the provided docker-compose.yml in the project root:

# Copy environment file
cp .env.example .env
# Edit .env with your development credentials

# Start all services
docker-compose up -d

# View logs
docker-compose logs -f api
docker-compose logs -f worker

Service Architecture

API Service: Handles HTTP requests, authentication, job management
- Memory: 2Gi, CPU: 2000m
- Autoscaling: 1-10 instances
- Public access via HTTPS
Worker Service: Processes video files with AI models
- Memory: 4Gi, CPU: 4000m
- Autoscaling: 0-5 instances
- Internal access only

Monitoring

Both services include:

OpenTelemetry tracing exported to Cloud Trace
Prometheus metrics for monitoring
Sentry error tracking for error reporting
Health checks for service reliability

Security

Services run with least-privilege service accounts
Secrets managed via Secret Manager
No hardcoded credentials in containers
Network isolation for worker service

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