Clean & Practical Redis Patterns in ASP.NET Core

A minimal yet professional backend application demonstrating three real-world Redis usage patterns in ASP.NET Core:

• ✅ Product listing caching
• ✅ Race condition prevention during concurrent operations
• ✅ Rate limiting to prevent API abuse

This project aims to go beyond basic Redis usage and showcase practical, production-like patterns with clean code and best practices.

🧰 Tech Stack

• .NET 9
• PostgreSQL (via Docker)
• Redis (via Docker)
• StackExchange.Redis
• Clean Architecture-style layering

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📦 Redis Patterns Implemented

1. Caching

• Product list data is cached with a configurable expiration.
• Redis is used as a distributed cache to improve response time and reduce DB load.

2. Race Condition Prevention

• During purchase attempts, a Redis key is used as a distributed lock.
• Ensures that product stock can’t go below zero even under concurrent requests.

3. Rate Limiting

• Requests are limited per IP using Redis sorted sets.
• Clients exceeding the threshold receive HTTP 429 - Too Many Requests.

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🚀 Getting Started

Prerequisites

• .NET 9 SDK
• Docker
• Docker Compose

Run the project

git clone https://github.com/sinanganiz/RedisPatternsInAspNetCore.git
cd RedisPatternsInAspNetCore
docker-compose up -d
dotnet run --project src/API/RedisPatterns.API

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🧪 Test the API

Rate Limiting Example

GET /api/Products

Call this endpoint more than 5 times within 1 minute to get 429 Too Many Requests.

Caching Example

GET /api/products

• First request fetches from DB and caches it.
• Subsequent requests hit Redis cache.

Purchase / Race Condition Simulation

POST /api/Purchase?productId={id}&quantity={quantity}

Safely decrements product stock using Redis locking.

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📘 API Documentation

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📊 Redis Insight Preview

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🗂️ Project Structure

src/
├── API/                  → ASP.NET Core API (entry point)
├── Application/          → Interfaces and services
├── Domain/               → Entities
├── Infrastructure/       → Redis, PostgreSQL setup
docker/
└── docker-compose.yml    → Redis & PostgreSQL containers