How and Why to Deploy a ReactJS Application in Azure Databricks Apps?

Why Deploy ReactJS Apps in Azure Databricks?

Deploying ReactJS apps using Azure Databricks Apps provides several key advantages:

• Scalability and Flexibility: Instantly scale applications with the underlying power of Databricks clusters.

• Integration with Big Data Ecosystem: Easily integrate your ReactJS applications with Databricks notebooks, Spark jobs, and data pipelines.

• Efficient Management: Simplify DevOps and reduce infrastructure overhead by leveraging Databricks’ managed services.

• Enhanced Collaboration: Collaborate effectively with teams directly within Databricks, maintaining seamless transitions between data science, engineering, and frontend development.

  
  

How to Deploy a ReactJS Application in Azure Databricks Apps

Follow these simplified steps to deploy your ReactJS application:

1. Set Up Your ReactJS Application

First, ensure your ReactJS application is production-ready:

npm run build

This command generates a build directory optimised for deployment.

2. Prepare the Azure Databricks Environment

• Log in to your Azure Databricks workspace.

• Create a new Databricks cluster or use an existing one tailored to your workload needs.

3. Upload Application Files to Databricks

• Navigate to your Databricks workspace and create a new directory.

• Upload your ReactJS build folder contents into this directory.

4. Create a Web App Notebook

In Databricks, create a notebook to serve your ReactJS app

from flask import Flask, send_from_directory

app = Flask(__name__, static_folder='your_react_build_folder')

@app.route('/', defaults={'path': ''})

@app.route('/<path:path>')

def serve(path):

    if path != "" and (app.static_folder / path).exists():

        return send_from_directory(app.static_folder, path)

    else:

        return send_from_directory(app.static_folder, 'index.html')

if __name__ == "__main__":

    app.run(host='0.0.0.0', port=8080)

Replace 'your_react_build_folder' with the path to your uploaded ReactJS build files.

5. Deployment configuration

To successfully deploy your application in the Databricks environment, you’ll need to configure it with the appropriate settings and dependencies.

Step1: App configuration

Start by creating an app.yaml file in the root directory of your project. This file defines the command used to launch your application within Databricks.

Create app.yaml and add the following content:

command: ['uvicorn', 'app:app', '--host', '0.0.0.0', '--port', '8000']

This configuration specifies that the app will be served using Uvicorn on port 8000.

Sep 2: Specifying Python Dependencies

Since Databricks runs in a Python-based environment, it’s essential to define your app’s dependencies. In this case, the app requires:

• FastAPI – to expose your application via HTTP endpoints

• Uvicorn – to run the FastAPI app as an ASGI server

Create a requirements.txt file in the root directory and include the following:

fastapi==0.115.12
uvicorn==0.34.2

6. Deploy the App Using Databricks Apps

To deploy your ReactJS app as a custom app in Azure Databricks:

• Navigate to the Databricks Apps section in your Databricks workspace.

• Select Create App to start configuring your custom application.

• Choose your previously created notebook (Web App Notebook) as the source notebook.

• Specify a unique name for your application and configure necessary settings such as compute requirements and runtime environment.

• Click on Deploy to finalise the creation of your app.

• Azure Databricks will handle the deployment, and once the process completes, it will provide you with a public URL to access your deployed ReactJS app.

Conclusion

Azure Databricks Apps transforms how you build, deploy, and scale full-stack applications by eliminating infrastructure silos and enabling seamless collaboration between frontend developers, data engineers, and data scientists. With built-in scalability, effortless API integration, and streamlined DevOps, it empowers you to create responsive, data-rich web apps without ever leaving your Databricks workspace.

If you're building modern applications that rely on real-time data, don't stop at the backend; take your ReactJS frontend live inside Databricks.

Click here and get started today, and turn your ReactJS front-end applications into complete, interactive web experiences that scale with your data.