description: "Deploy your Databricks app to production"

Deploy to Databricks Apps

I'll deploy your Databricks app to production with comprehensive validation and monitoring.

What I'll do:

1. Validate environment - Check authentication and configuration
2. Test locally first - Run app locally to catch issues before deployment
3. Check app status - Verify if app exists or needs creation
4. Deploy to Databricks - Build, sync, and deploy using proper workflow
5. Monitor deployment - Verify successful deployment and provide URL
6. Provide next steps - Give you monitoring and debugging information

Deployment Workflow

Step 1: Environment Validation

# Check if .env.local exists and is configured
cat .env.local

# Test Databricks authentication
databricks current-user me

Step 2: Local Testing (Critical)

# Test app locally first to catch issues
./run_app_local.sh

Step 3: App Status Check

# Check if app exists
./app_status.sh

# Get app details
databricks apps get "$DATABRICKS_APP_NAME"

Step 4: Deployment Decision

Based on app status:

• If app exists: Deploy with ./deploy.sh
• If app doesn't exist: Ask if you want to create it
• If you want to create: Use ./deploy.sh --create

Step 5: Deploy

# Deploy (with creation if needed)
./deploy.sh --create --verbose

Step 6: Deployment Verification

# Check final status
./app_status.sh

# Verify app is running
databricks apps get "$DATABRICKS_APP_NAME"

Deployment Options

Standard Deployment:

./deploy.sh

Create New App:

./deploy.sh --create

Verbose Deployment:

./deploy.sh --verbose

What Happens During Deployment

1. Authentication - Validates Databricks credentials
2. App Creation - Creates app if using --create and doesn't exist
3. Frontend Build - Builds React app for production
4. Requirements Generation - Creates requirements.txt from pyproject.toml
5. Workspace Sync - Uploads source code to Databricks workspace
6. App Deployment - Deploys via Databricks CLI
7. Verification - Confirms successful deployment

Monitoring Your Deployment

Check App Status:

./app_status.sh

View Deployment Logs:

• Visit your app URL + /logz in browser
• Requires OAuth authentication
• Cannot be accessed via curl

Debug Deployment Issues:

# Get verbose status
./app_status.sh --verbose

# Check workspace files
databricks workspace list "$DBA_SOURCE_CODE_PATH"

Common Deployment Issues

Authentication Problems:

• Check .env.local configuration
• Test with databricks current-user me
• Reconfigure with ./setup.sh

App Creation Issues:

• Verify you have app creation permissions
• Check if app name is available
• Use ./deploy.sh --create explicitly

Build/Import Errors:

• Test locally first with ./run_app_local.sh
• Check TypeScript compilation
• Verify all dependencies are installed

Deployment Failures:

• Check app logs at URL + /logz
• Use ./app_status.sh --verbose for details
• Verify workspace file sync

Success Criteria

Deployment is successful when:

• ✅ App status shows "RUNNING"
• ✅ App URL returns 200 OK
• ✅ No errors in /logz endpoint
• ✅ App functionality works as expected

Next Steps After Deployment

1. Test your app at the provided URL
2. Monitor logs via /logz endpoint
3. **Use /status** to check health regularly
4. **Use /debug** if issues arise
5. Iterate and deploy as needed

Your app is now live! 🚀