Redis Patterns

A solid reference for the Redis patterns you actually need in production: cache-aside vs write-through, distributed locks with proper token-based release, sliding window rate limiting with Lua scripts, and when to pick Streams over Pub/Sub. The data structure cheat sheet alone will save you from reinventing session storage as a JSON blob in a string. Covers the essentials like connection pooling, TTL strategies, and key naming conventions that prevent your cache from turning into a memory leak. Light on theory, heavy on copy-paste-adapt code. If you're adding Redis to an app and don't want to relearn the difference between INCR and ZADD every six months, this gets you there quickly.

skills.sh installs: 5.7K
GitHub stars: 300.3K
last updated: Aug 21, 2026

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Install

$ npx -y skills add affaan-m/ecc --skill redis-patterns --agent claude-code

Installs into .claude/skills of the current project.

Files

Redis Patterns

Quick reference for Redis best practices across common backend use cases.

How It Works

Redis is an in-memory data structure store that supports strings, hashes, lists, sets, sorted sets, streams, and more. Individual Redis commands are atomic on a single instance; multi-step workflows require Lua scripts, MULTI/EXEC transactions, or explicit synchronization to stay atomic. Data is optionally persisted via RDB snapshots or AOF logs. Clients communicate over TCP using the RESP protocol; connection pools are essential to avoid per-request handshake overhead.