Brickhouse Brands Demo 🥤

A demonstration inventory management dashboard showcasing modern full-stack architecture with React frontend, FastAPI backend, and PostgreSQL (Lakebase) database. This is a demonstration application only and is not intended for production use. Designed to showcase deployment patterns on Databricks Apps with local development support.

⚠️ Disclaimer: This is a demonstration application designed for educational and showcase purposes only. It is not intended for production use, real business operations, or as a comprehensive enterprise solution. All data, performance metrics, and features are simulated for demonstration purposes.

📒 Table of Contents

📊 Application Features
🏗️ Architecture
🚀 Quick Start
🔐 Production Deployment with Databricks
- Setting Up Databricks Secrets
- Deploy to Databricks Apps
📁 Project Structure
🛠️ Development
- Local Development Commands
📈 Future Considerations
ℹ️ How to get help
🤝 Contributing
License

📊 Application Features

Dashboard Overview

Real-time KPI cards with inventory metrics
Interactive charts for sales and inventory trends
Regional filtering and performance analytics

Inventory Management

Basic CRUD operations for products and stock levels
Low stock alerts and sample reordering suggestions
Category-based product organization

Order Management

Sample order lifecycle with approval workflows
Basic order processing and fulfillment tracking
Demo manager approval system with role-based permissions

Store Management

Multi-location inventory tracking
Regional performance comparisons
Store type categorization (retail vs warehouse)

Performance Testing & Simulation

Sample Rust-based traffic simulator for database load testing demonstrations
Example query patterns simulating business operations (SELECT, INSERT, UPDATE)
Configurable concurrent connections and traffic intensity levels
Sample traffic patterns: Business Hours, E-Commerce Rush, Nightly Batch processing
Basic performance metrics: throughput, latency analysis, connection efficiency

🏗️ Architecture

This project demonstrates a sample application architecture with centralized configuration management:

Frontend: React + TypeScript with shadcn/ui components and Vite build system
Backend: FastAPI with PostgreSQL integration and RESTful API design
Database: PostgreSQL with automated setup scripts and demo data generation
Traffic Simulator: Sample Rust application for database load testing demonstrations
Deployment: Databricks Apps deployment showcase with secret management examples

Key Features

Centralized Configuration: Single .env file synced across all components
Automated Setup: One-command environment setup and development server startup
Demo Deployment: Databricks Apps deployment example with secret management
Sample Dashboard: Interactive analytics demo with inventory management and order tracking

🚀 Quick Start

Prerequisites

Node.js 18+ for frontend development
Python 3.10+ for backend and database setup
Rust 1.70+ for traffic simulator application (optional)
PostgreSQL database instance (16+ recommended)
Databricks CLI for production deployment to a Databricks Apps environment

1. Databricks CLI Authentication

First, install and authenticate with the Databricks CLI:

# Authenticate with your Databricks workspace and set profile
databricks auth login --host <databricks-workspace-url> --profile <my-profile>

# Verify authentication
databricks auth describe --profile <my-profile>

For installation instructions, see the official Databricks CLI installation guide.

2. Local Environment Setup

Run the setup script to configure all components:

./setup-env.sh

This script will:

Create Python virtual environments for backend and database components
Install all dependencies (npm packages and pip requirements)
Copy .env file from the project root across all components
Verify prerequisites and system compatibility

3. Configuration

Edit the root .env file with your actual configuration:

# Copy from template if not already created
cp env.example .env

# Edit with your settings
vim .env  # or your preferred editor

Environment Variables

Variable	Description	Example
`DB_HOST`	PostgreSQL host	`localhost`
`DB_PORT`	PostgreSQL port	`5432`
`DB_NAME`	Database name	`databricks_postgres`
`DB_USER`	Database username	`your_username`
`DB_PASSWORD`	Database password	`your_password`
`DATABRICKS_HOST`	Databricks workspace URL	`https://your-workspace.cloud.databricks.com`
`DATABRICKS_TOKEN`	Personal access token / PAT (optional)	`your_token`
`DATABRICKS_CLIENT_ID`	Databricks client id (instead of PAT) (optional)	`your_client_id`
`DATABRICKS_CLIENT_SECRET`	Databricks client id (instead of PAT) (optional)	`your_client_secret`

NB - we recommend running setup-env.sh if any modifications are made to the environment file

4. Database Setup

Create Database Service Account (Recommended)

If you are using Lakebase Postgres, please ensure that Postgres Native Role Login = Enabled - this may require a restart of your Lakebase instance once updated in order to support static username & password based credentials.

We recommend creating a dedicated service account for database interactions:

-- Create dedicated service account
CREATE USER api_service_account WITH 
    ENCRYPTED PASSWORD 'SomeSecurePassword123'
    LOGIN
    NOCREATEDB 
    NOCREATEROLE;

-- Grant database connection
GRANT CONNECT ON DATABASE databricks_postgres TO api_service_account;

-- Create analytics schema (admin only - requires CREATE privileges)
CREATE SCHEMA IF NOT EXISTS analytics;

-- Grant schema usage and create permissions
GRANT USAGE, CREATE ON SCHEMA public TO api_service_account;
GRANT USAGE, CREATE ON SCHEMA analytics TO api_service_account;

-- Grant table permissions
GRANT SELECT, INSERT, UPDATE, DELETE ON ALL TABLES IN SCHEMA public TO api_service_account;

-- Grant sequence permissions (for auto-increment columns)
GRANT USAGE, SELECT ON ALL SEQUENCES IN SCHEMA public TO api_service_account;

-- Set default privileges for future objects
ALTER DEFAULT PRIVILEGES IN SCHEMA public 
GRANT SELECT, INSERT, UPDATE, DELETE ON TABLES TO api_service_account;

ALTER DEFAULT PRIVILEGES IN SCHEMA public 
GRANT USAGE, SELECT ON SEQUENCES TO api_service_account;

-- Grant analytics schema permissions for materialized views
ALTER DEFAULT PRIVILEGES IN SCHEMA analytics 
GRANT SELECT ON TABLES TO api_service_account;

Update your .env file to use the service account credentials:

DB_USER=api_service_account
DB_PASSWORD=SomeSecurePassword123

Initialize Database with Demo Data

Initialize the database with demo data:

cd database
source venv/bin/activate
python demo_setup.py

This creates all necessary tables and populates them with realistic demo data including:

50+ beverage products across multiple categories
20+ store locations across 4 US regions
240K+ orders with realistic approval workflows
User accounts for store and regional managers

5. Start Development Environment

Launch both frontend and backend servers:

./start-dev.sh

The application will be available at:

Frontend: http://localhost:5173
Backend API: http://localhost:8000
API Documentation: http://localhost:8000/docs

🔐 Demo Deployment with Databricks

Setting Up Databricks Secrets

For demonstration deployment, database credentials are managed through Databricks secrets.
Set up the required secrets using the Databricks CLI as follows:

# Create secret scope
databricks secrets create-scope brickhouse-scope --profile <my-profile>

# Set database credentials as secrets
databricks secrets put-secret brickhouse-scope db_host --string-value "your-db-host" --profile <my-profile>
databricks secrets put-secret brickhouse-scope db_user --string-value "your-db-username" --profile <my-profile>
databricks secrets put-secret brickhouse-scope db_password --string-value "your-db-password" --profile <my-profile>

# Verify secrets are created
databricks secrets list-secrets brickhouse-scope --profile <my-profile>

Deploy to Databricks Apps

Use the deployment script for demonstration:

# Deploy demo app under given Databricks CLI profile and prod target via Databricks Asset Bundles.
./deploy.sh --profile my-profile --target prod

The deployment script demonstrates:

Building the React frontend for deployment
Copying frontend assets to backend static files
Deploying the application bundle to Databricks
Starting the application using Databricks Apps

📁 Project Structure

brickhouse-brands-demo/
├── frontend/              # React + TypeScript frontend
│   ├── src/              # Source code
│   ├── dist/             # Production build output
│   └── package.json      # Frontend dependencies
├── backend/              # FastAPI backend
│   ├── app/              # Application modules
│   ├── static/           # Frontend assets (after build)
│   ├── main.py           # FastAPI application
│   └── requirements.txt  # Python dependencies
├── database/             # Database setup and management
│   ├── demo_setup.py     # Database initialization script
│   └── requirements.txt  # Database tool dependencies
├── traffic-simulator/    # Rust-based database traffic simulator
│   ├── src/              # Rust source code
│   ├── target/           # Compiled binaries
│   ├── Cargo.toml        # Rust dependencies
│   ├── run_simulation.sh # Quick simulation script
│   └── README.md         # Detailed usage instructions
├── setup-env.sh          # Environment setup script
├── start-dev.sh          # Development server startup
├── deploy.sh             # Production deployment script
├── databricks.yml        # Databricks bundle configuration
└── env.example          # Environment variables template

🛠️ Development

Each component has its own focused README with specific development instructions:

Frontend: See frontend/README.md for React development details
Backend: See backend/README.md for FastAPI API documentation
Database: See database/README.md for schema and setup details
Traffic Simulator: See traffic-simulator/README.md for performance testing and simulation usage

Local Development Commands

# Setup everything
./setup-env.sh

# Start development servers
./start-dev.sh

# Manual component startup
cd backend && source venv/bin/activate && python startup.py
cd frontend && npm run dev

# Database setup and data generation
cd database && source venv/bin/activate && python demo_setup.py --dry-run

# Traffic simulation (requires Rust and database setup)
cd traffic-simulator && ./run_simulation.sh

📈 Educational Extensions

This demo application could be extended for learning purposes with:

Custom Business Logic: Example API extensions with additional requirements
Enhanced Analytics: Sample reporting and dashboard patterns
Integration Examples: Demonstrations of external system connections
Scaling Patterns: Examples of multi-workspace deployment patterns
Authentication Examples: Sample user management with On-Behalf-Of Auth workflow and Unity Catalog patterns

Note: Any extensions should maintain the demonstration/educational focus and not be used for production workloads.

ℹ️ How to get help

Databricks support doesn't cover this content. For questions or bugs, please open a GitHub issue and the team will help on a best effort basis. Contributions are more than welcome!

🤝 Contributing

Fork the repository
Create a feature branch (git checkout -b feature/amazing-feature)
Run the setup script to configure your development environment
Make your changes and test thoroughly
Commit your changes (git commit -m 'Add amazing feature')
Push to the branch (git push origin feature/amazing-feature)
Open a Pull Request

License

© 2025 Databricks, Inc. All rights reserved. The source in this repository is provided subject to the Databricks License.
All included or referenced third party libraries are subject to the licenses set forth below.

Frontend Dependencies

library	description	license	source
react	JavaScript library for building user interfaces	MIT	https://github.com/facebook/react
typescript	Typed superset of JavaScript	Apache-2.0	https://github.com/microsoft/TypeScript
vite	Next generation frontend build tool	MIT	https://github.com/vitejs/vite
tailwindcss	Utility-first CSS framework	MIT	https://github.com/tailwindlabs/tailwindcss
@radix-ui/react-*	Low-level UI primitives and components	MIT	https://github.com/radix-ui/primitives
@tanstack/react-query	Powerful data synchronization for React	MIT	https://github.com/TanStack/query
axios	Promise-based HTTP client	MIT	https://github.com/axios/axios
react-router-dom	Declarative routing for React	MIT	https://github.com/remix-run/react-router
react-hook-form	Performant forms with easy validation	MIT	https://github.com/react-hook-form/react-hook-form
zod	TypeScript-first schema validation	MIT	https://github.com/colinhacks/zod
zustand	Small, fast and scalable state management	MIT	https://github.com/pmndrs/zustand
lucide-react	Beautiful and customizable SVG icons	ISC	https://github.com/lucide-icons/lucide
recharts	Redefined chart library built with React and D3	MIT	https://github.com/recharts/recharts
cmdk	Fast, unstyled command menu	MIT	https://github.com/pacocoursey/cmdk
class-variance-authority	CSS class variance API	Apache-2.0	https://github.com/joe-bell/cva
clsx	Utility for constructing className strings	MIT	https://github.com/lukeed/clsx
date-fns	Modern JavaScript date utility library	MIT	https://github.com/date-fns/date-fns

Backend Dependencies

library	description	license	source
fastapi	Modern, fast web framework for building APIs with Python	MIT	https://github.com/tiangolo/fastapi
uvicorn	Lightning-fast ASGI server	BSD-3-Clause	https://github.com/encode/uvicorn
pydantic	Data validation using Python type annotations	MIT	https://github.com/pydantic/pydantic
psycopg2-binary	PostgreSQL database adapter for Python	LGPL-3.0	https://github.com/psycopg/psycopg2
python-dotenv	Read key-value pairs from .env file	BSD-3-Clause	https://github.com/theskumar/python-dotenv
python-multipart	Streaming multipart parser for Python	Apache-2.0	https://github.com/andrew-d/python-multipart
databricks-sdk	Databricks SDK for Python	Apache-2.0	https://github.com/databricks/databricks-sdk-py
databricks-sql-connector	Databricks SQL Connector for Python	Apache-2.0	https://github.com/databricks/databricks-sql-python
aiofiles	File support for asyncio	Apache-2.0	https://github.com/Tinche/aiofiles

Database & Data Generation Dependencies

library	description	license	source
psycopg2-binary	PostgreSQL database adapter for Python	LGPL-3.0	https://github.com/psycopg/psycopg2
faker	Python package that generates fake data	MIT	https://github.com/joke2k/faker
tqdm	Fast, extensible progress bar for Python	MPL-2.0 & MIT	https://github.com/tqdm/tqdm
python-dateutil	Extensions to the standard Python datetime module	Apache-2.0 & BSD-3-Clause	https://github.com/dateutil/dateutil
numpy	Fundamental package for scientific computing	BSD-3-Clause	https://github.com/numpy/numpy
black	Code formatter for Python	MIT	https://github.com/psf/black

Traffic Simulator (Rust) Dependencies

library	description	license	source
anyhow	Flexible concrete Error type built on std::error::Error	MIT OR Apache-2.0	https://github.com/dtolnay/anyhow
chrono	Date and time library for Rust	MIT OR Apache-2.0	https://github.com/chronotope/chrono
clap	Command line argument parser	MIT OR Apache-2.0	https://github.com/clap-rs/clap
deadpool-postgres	Dead simple async pool for PostgreSQL	MIT OR Apache-2.0	https://github.com/bikeshedder/deadpool
futures	Asynchronous programming for Rust	MIT OR Apache-2.0	https://github.com/rust-lang/futures-rs
native-tls	TLS/SSL streams for Rust	MIT OR Apache-2.0	https://github.com/sfackler/rust-native-tls
postgres-native-tls	TLS support for postgres via native-tls	MIT OR Apache-2.0	https://github.com/sfackler/rust-postgres
rand	Random number generators and other randomness functionality	MIT OR Apache-2.0	https://github.com/rust-random/rand
rand_distr	Sampling from random number distributions	MIT OR Apache-2.0	https://github.com/rust-random/rand
serde	Serialization framework for Rust	MIT OR Apache-2.0	https://github.com/serde-rs/serde
tokio	Asynchronous runtime for Rust	MIT OR Apache-2.0	https://github.com/tokio-rs/tokio
tokio-postgres	Native PostgreSQL driver for Rust	MIT OR Apache-2.0	https://github.com/sfackler/rust-postgres
tracing	Application-level tracing for Rust	MIT OR Apache-2.0	https://github.com/tokio-rs/tracing
tracing-subscriber	Utilities for implementing and composing tracing subscribers	MIT OR Apache-2.0	https://github.com/tokio-rs/tracing
uuid	Generate and parse UUIDs	MIT OR Apache-2.0	https://github.com/uuid-rs/uuid

Name		Name	Last commit message	Last commit date
Latest commit History 42 Commits
backend		backend
database		database
frontend		frontend
traffic-simulator		traffic-simulator
.gitignore		.gitignore
.tool-versions		.tool-versions
CODEOWNERS.txt		CODEOWNERS.txt
LICENSE.md		LICENSE.md
NOTICE.md		NOTICE.md
README.md		README.md
SECURITY.md		SECURITY.md
databricks.yml		databricks.yml
deploy.sh		deploy.sh
env.example		env.example
setup-env.sh		setup-env.sh
start-dev.sh		start-dev.sh

License

databricks-solutions/brickhouse-brands-demo

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Brickhouse Brands Demo 🥤

📒 Table of Contents

📊 Application Features

Dashboard Overview

Inventory Management

Order Management

Store Management

Performance Testing & Simulation

🏗️ Architecture

Key Features

🚀 Quick Start

Prerequisites

1. Databricks CLI Authentication

2. Local Environment Setup

3. Configuration

Environment Variables

4. Database Setup

Create Database Service Account (Recommended)

Initialize Database with Demo Data

5. Start Development Environment

🔐 Demo Deployment with Databricks

Setting Up Databricks Secrets

Deploy to Databricks Apps

📁 Project Structure

🛠️ Development

Local Development Commands

📈 Educational Extensions

ℹ️ How to get help

🤝 Contributing

License

Frontend Dependencies

Backend Dependencies

Database & Data Generation Dependencies

Traffic Simulator (Rust) Dependencies

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