Showcase Your Redis Skills with a GitHub README Badge

Use this markdown in your README:

![Redis](https://img.shields.io/badge/Redis-DC382D?style=for-the-badge&logo=redis&logoColor=white)

The #DC382D is Redis's official red. The redis logo identifier renders the Redis cube logo from Simple Icons. This red badge pairs naturally with backend technology stacks — especially alongside Node.js, Python, and database tools.

Redis has diverse use cases — knowing which ones you have production experience with demonstrates real depth. Key Redis patterns to mention specifically:

• Caching: Reducing database load with TTL-based cache invalidation
• Session storage: Fast user session reads for web applications
• Rate limiting: Using Redis atomic operations (INCR + EXPIRE) to enforce API limits
• Message queuing: Redis Streams or Pub/Sub for real-time event distribution
• Leaderboards: Sorted Sets for real-time ranking systems
• Distributed locks: Using SETNX for distributed system coordination

Each of these patterns represents a different aspect of Redis mastery. Even two or three of these in a specific description signals genuine production Redis usage.

Redis appears across multiple technology stacks:

• Node.js API stack: Redis + Node.js + Express + PostgreSQL
• Python backend stack: Redis + FastAPI/Django + Celery + PostgreSQL
• Microservices stack: Redis + Docker + Kubernetes + RabbitMQ
• Real-time stack: Redis + Socket.io + Node.js + MongoDB

Redis Cluster and Redis Sentinel (for high availability) are advanced topics worth mentioning if you have production experience with them. These signal infrastructure-level Redis knowledge rather than simple cache-get/cache-set usage.

Redis configuration work is done in shell scripts, Python, or JavaScript — your top languages will reflect your application language rather than Redis itself. Redis commands are typically abstracted through client libraries (ioredis for Node.js, redis-py for Python, Jedis for Java).

For pinned repositories, include projects that demonstrate Redis as a meaningful architectural component: an API with Redis caching that shows measurably improved response times, a rate limiter implementation, or a real-time feature using Pub/Sub. A benchmark showing cached vs. uncached response times in a repository's README is particularly compelling for engineers evaluating your Redis understanding.