Google Cloud Run Deployment Guide

Complete guide for deploying the LangChain Agent MCP Server to Google Cloud Run.

Prerequisites

Google Cloud Account with billing enabled
Google Cloud SDK (gcloud) installed and configured
Docker installed and running
OpenAI API Key ready to configure

Quick Start

Option 1: Using Deployment Scripts (Recommended)

Windows PowerShell (Recommended for Windows users):

.\deploy-cloud-run.ps1 -ProjectId "your-project-id" -Region "us-central1"

📖 For detailed Windows instructions, see DEPLOY_CLOUD_RUN_WINDOWS.md

Linux/Mac:

chmod +x deploy-cloud-run.sh
./deploy-cloud-run.sh your-project-id us-central1

Option 2: Manual Deployment

Follow the step-by-step instructions below.

Step-by-Step Deployment

1. Install and Configure Google Cloud SDK

# Install gcloud CLI (if not already installed)
# See: https://cloud.google.com/sdk/docs/install

# Authenticate
gcloud auth login

# Set your project
gcloud config set project YOUR_PROJECT_ID

2. Enable Required APIs

gcloud services enable cloudbuild.googleapis.com
gcloud services enable run.googleapis.com
gcloud services enable containerregistry.googleapis.com

3. Build and Push Docker Image

# Set variables
PROJECT_ID="your-project-id"
SERVICE_NAME="langchain-agent-mcp-server"
IMAGE_NAME="gcr.io/${PROJECT_ID}/${SERVICE_NAME}"

# Build the image
docker build -t $IMAGE_NAME .

# Push to Container Registry
docker push $IMAGE_NAME

4. Deploy to Cloud Run

gcloud run deploy $SERVICE_NAME \
    --image $IMAGE_NAME \
    --platform managed \
    --region us-central1 \
    --allow-unauthenticated \
    --memory 2Gi \
    --cpu 2 \
    --timeout 300 \
    --max-instances 10 \
    --min-instances 0 \
    --set-env-vars "OPENAI_MODEL=gpt-4o-mini,MAX_ITERATIONS=10,VERBOSE=false" \
    --port 8000

5. Configure OpenAI API Key

Option A: Using Environment Variable (Quick but less secure)

gcloud run services update $SERVICE_NAME \
    --set-env-vars OPENAI_API_KEY=your-key-here \
    --region us-central1

Option B: Using Secret Manager (Recommended for production)

Create a secret:

echo -n "your-openai-api-key" | gcloud secrets create openai-api-key \
    --data-file=- \
    --replication-policy="automatic"

Grant Cloud Run access to the secret:

PROJECT_NUMBER=$(gcloud projects describe $PROJECT_ID --format="value(projectNumber)")
gcloud secrets add-iam-policy-binding openai-api-key \
    --member="serviceAccount:${PROJECT_NUMBER}-compute@developer.gserviceaccount.com" \
    --role="roles/secretmanager.secretAccessor"

Update the service to use the secret:

gcloud run services update $SERVICE_NAME \
    --update-secrets=OPENAI_API_KEY=openai-api-key:latest \
    --region us-central1

6. Verify Deployment

# Get the service URL
SERVICE_URL=$(gcloud run services describe $SERVICE_NAME \
    --platform managed \
    --region us-central1 \
    --format 'value(status.url)')

# Test health endpoint
curl $SERVICE_URL/health

# Test manifest endpoint
curl $SERVICE_URL/mcp/manifest

Configuration Options

Resource Allocation

Adjust based on your needs:

# For higher traffic or complex queries
--memory 4Gi \
--cpu 4 \
--max-instances 20

# For cost optimization
--memory 1Gi \
--cpu 1 \
--max-instances 5 \
--min-instances 0  # Scale to zero when not in use

Timeout Settings

Cloud Run has a maximum timeout of 300 seconds (5 minutes). For longer-running agent tasks:

--timeout 300  # Maximum allowed

Environment Variables

Set additional environment variables:

gcloud run services update $SERVICE_NAME \
    --set-env-vars "OPENAI_MODEL=gpt-4,MAX_ITERATIONS=15,VERBOSE=true,API_KEY=your-api-key" \
    --region us-central1

CORS Configuration

If you need to allow specific origins:

gcloud run services update $SERVICE_NAME \
    --set-env-vars "CORS_ORIGINS=https://yourdomain.com,https://app.yourdomain.com" \
    --region us-central1

Using Cloud Build (CI/CD)

1. Create cloudbuild.yaml

The cloudbuild.yaml file is already included in the repository. It:

Builds the Docker image
Pushes to Container Registry
Deploys to Cloud Run

2. Set up Cloud Build Trigger

# Create a trigger for GitHub
gcloud builds triggers create github \
    --name="deploy-langchain-mcp" \
    --repo-name="LangchainMCP" \
    --repo-owner="mcpmessenger" \
    --branch-pattern="^main$" \
    --build-config="cloudbuild.yaml"

3. Set Secrets in Cloud Build

# Store OpenAI API key as a secret
echo -n "your-openai-api-key" | gcloud secrets create openai-api-key \
    --data-file=-

# Grant Cloud Build access
PROJECT_NUMBER=$(gcloud projects describe $PROJECT_ID --format="value(projectNumber)")
gcloud secrets add-iam-policy-binding openai-api-key \
    --member="serviceAccount:${PROJECT_NUMBER}@cloudbuild.gserviceaccount.com" \
    --role="roles/secretmanager.secretAccessor"

4. Update cloudbuild.yaml to use secrets

Add this step before the deploy step:

- name: 'gcr.io/google.com/cloudsdktool/cloud-sdk'
  entrypoint: 'bash'
  args:
    - '-c'
    - |
      gcloud run services update langchain-agent-mcp-server \
        --update-secrets=OPENAI_API_KEY=openai-api-key:latest \
        --region us-central1

Monitoring and Logging

View Logs

# View recent logs
gcloud run services logs read $SERVICE_NAME \
    --platform managed \
    --region us-central1

# Follow logs in real-time
gcloud run services logs tail $SERVICE_NAME \
    --platform managed \
    --region us-central1

Set up Monitoring

Go to Cloud Console → Cloud Run → Your Service
Click on "Monitoring" tab
Set up alerts for:
- Request latency
- Error rate
- Memory usage
- CPU usage

Cost Optimization

1. Scale to Zero

--min-instances 0  # Scales down when not in use

2. Use Appropriate Resources

Start with minimal resources and scale up as needed:

Development: 1 CPU, 1Gi memory
Production: 2 CPU, 2Gi memory
High Traffic: 4 CPU, 4Gi memory

3. Set Request Limits

--max-instances 10  # Limit concurrent instances

4. Use Cloud Run Pricing Calculator

Estimate costs: https://cloud.google.com/run/pricing

Troubleshooting

Service Won't Start

Check logs:

gcloud run services logs read $SERVICE_NAME --region us-central1

Verify environment variables:

gcloud run services describe $SERVICE_NAME --region us-central1

Test locally with Docker:

docker run -p 8000:8000 -e OPENAI_API_KEY=your-key gcr.io/$PROJECT_ID/$SERVICE_NAME

High Latency

Increase memory/CPU:

gcloud run services update $SERVICE_NAME \
    --memory 4Gi --cpu 4 --region us-central1

Check agent iteration limits:

gcloud run services update $SERVICE_NAME \
    --set-env-vars MAX_ITERATIONS=5 --region us-central1

Authentication Issues

If you need to restrict access:

# Remove --allow-unauthenticated and use IAM
gcloud run services update $SERVICE_NAME \
    --no-allow-unauthenticated \
    --region us-central1

# Grant access to specific users
gcloud run services add-iam-policy-binding $SERVICE_NAME \
    --member="user:email@example.com" \
    --role="roles/run.invoker" \
    --region us-central1

Security Best Practices

Use Secret Manager for API keys (not environment variables)
Enable VPC if accessing private resources
Set up IAM policies for service access
Enable Cloud Armor for DDoS protection
Use HTTPS only (enabled by default)
Set up API key authentication in the application

Next Steps

Set up custom domain: https://cloud.google.com/run/docs/mapping-custom-domains
Configure CDN: Use Cloud CDN with Cloud Run
Set up monitoring: Configure alerts in Cloud Monitoring
Enable tracing: Use Cloud Trace for request tracing

Support

For issues or questions:

Check Cloud Run logs
Review Cloud Run documentation
Check application logs in Cloud Console

Provide feedback

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Google Cloud Run Deployment Guide

Prerequisites

Quick Start

Option 1: Using Deployment Scripts (Recommended)

Option 2: Manual Deployment

Step-by-Step Deployment

1. Install and Configure Google Cloud SDK

2. Enable Required APIs

3. Build and Push Docker Image

4. Deploy to Cloud Run

5. Configure OpenAI API Key

6. Verify Deployment

Configuration Options

Resource Allocation

Timeout Settings

Environment Variables

CORS Configuration

Using Cloud Build (CI/CD)

1. Create cloudbuild.yaml

2. Set up Cloud Build Trigger

3. Set Secrets in Cloud Build

4. Update cloudbuild.yaml to use secrets

Monitoring and Logging

View Logs

Set up Monitoring

Cost Optimization

1. Scale to Zero

2. Use Appropriate Resources

3. Set Request Limits

4. Use Cloud Run Pricing Calculator

Troubleshooting

Service Won't Start

High Latency

Authentication Issues

Security Best Practices

Next Steps

Support

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Google Cloud Run Deployment Guide

Prerequisites

Quick Start

Option 1: Using Deployment Scripts (Recommended)

Option 2: Manual Deployment

Step-by-Step Deployment

1. Install and Configure Google Cloud SDK

2. Enable Required APIs

3. Build and Push Docker Image

4. Deploy to Cloud Run

5. Configure OpenAI API Key

6. Verify Deployment

Configuration Options

Resource Allocation

Timeout Settings

Environment Variables

CORS Configuration

Using Cloud Build (CI/CD)

1. Create cloudbuild.yaml

2. Set up Cloud Build Trigger

3. Set Secrets in Cloud Build

4. Update cloudbuild.yaml to use secrets

Monitoring and Logging

View Logs

Set up Monitoring

Cost Optimization

1. Scale to Zero

2. Use Appropriate Resources

3. Set Request Limits

4. Use Cloud Run Pricing Calculator

Troubleshooting

Service Won't Start

High Latency

Authentication Issues

Security Best Practices

Next Steps

Support