Deploy to databricks apps

--- 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 ``bash # Check if .env.local exists and is configured cat .env.local # Test Databricks authentication databricks current-user me ` **Step 2: Local Testing (Critical)** `bash # Test app locally first to catch issues ./run_app_local.sh ` **Step 3: App Status Check** `bash # Check if app exists ./app_status.sh # Get app details databricks apps get "$DATABRICKS_APP_NAME" ` **Step 4: Deployment Decision** Based on app status: - **If app exists**: Deploy with ./deploy.sh - **If app doesn't exist**: Ask if you want to create it - **If you want to create**: Use ./deploy.sh --create **Step 5: Deploy** `bash # Deploy (with creation if needed) ./deploy.sh --create --verbose ` **Step 6: Deployment Verification** `bash # Check final status ./app_status.sh # Verify app is running databricks apps get "$DATABRICKS_APP_NAME" ` ## Deployment Options **Standard Deployment:** `bash ./deploy.sh ` **Create New App:** `bash ./deploy.sh --create ` **Verbose Deployment:** `bash ./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:** `bash ./app_status.sh ` **View Deployment Logs:** - Visit your app URL + /logz in browser - Requires OAuth authentication - Cannot be accessed via curl **Debug Deployment Issues:** `bash # 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 ./runapplocal.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! 🚀