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Redis

Redis as cache, session store, message broker, rate limiter, and distributed lock — production patterns and best practices.

What is Redis?

Redis is one of 70 specialized agent skills built into the Multos AI platform. When you describe a task related to data, this skill activates automatically — bringing domain-specific knowledge about redis, cache, session store, pub sub, rate limiting, distributed lock directly into your development workflow.

Generates implementations for cache-aside with TTL/invalidation, distributed rate limiting with sliding windows, session storage, pub/sub, sorted sets for leaderboards, and Redis Streams for event sourcing. Handles connection pooling, cluster mode, and circuit breaker patterns.

Key Capabilities

  • Generates complete, working implementations for redis with proper error handling and edge cases
  • Understands best practices and security patterns specific to data development
  • Provides step-by-step guidance from setup through production deployment
  • Adapts to your existing codebase — works with any framework, language, or architecture
  • Generates tests alongside implementation code to ensure reliability
  • Specialized knowledge of cache patterns, common pitfalls, and optimization techniques

How to Use Redis on Multos AI

Example Prompts

  • "Add Redis caching with proper invalidation strategy"
  • "Build a distributed rate limiter using sliding window"
  • "Implement a real-time leaderboard with sorted sets"

Example Output

async function rateLimit(userId: string, limit: number, windowSec: number) {
  const key = `rate:${userId}`;
  const now = Date.now();
  const pipeline = redis.pipeline();
  pipeline.zremrangebyscore(key, 0, now - windowSec * 1000);
  pipeline.zadd(key, now, `${now}-${crypto.randomUUID()}`);
  pipeline.zcard(key);
  pipeline.expire(key, windowSec);
  const results = await pipeline.exec();
  return (results[2][1] as number) <= limit;
}

Real-World Use Case

A social platform with 50K concurrent users implemented sorted-set leaderboards, pub/sub notifications, and sliding-window rate limiting — reducing database load by 70% while keeping feeds fresh in real-time.

Frequently Asked Questions

What is the Redis skill in Multos AI?

The Redis skill is a specialized AI capability within Multos AI that redis as cache, session store, message broker, rate limiter, and distributed lock — production patterns and best practices. It activates automatically when your prompt relates to data tasks, providing expert-level guidance and production-ready code.

Do I need to configure Redis manually?

No. Multos AI uses intent detection to activate the Redis skill automatically when your request involves redis. There's no setup, no plugins to install, and no configuration files to manage.

Which AI models work best with Redis?

All 33 models on Multos AI can leverage the Redis skill. For complex data tasks, we recommend models with larger context windows like Claude Opus 4.6 (1M tokens) or Gemini 3.1 Pro (1M tokens). For quick iterations, faster models like GPT-5.4 Mini or Claude Haiku 4.5 work well.

Can I use Redis with my existing project?

Yes. You can connect your GitHub, GitLab, or Bitbucket repository to Multos AI and the Redis skill will work with your existing codebase. It understands your project structure, dependencies, and coding patterns to provide contextual assistance.

Is Redis available on the free plan?

Yes, all 70 agent skills including Redis are available on every plan. Free users get access to lite-tier models, while paid plans unlock more powerful models for complex data tasks.

Works Great With

Related Data Skills

Build with Redis on Multos AI

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