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redis-expert skill

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This skill provides expert guidance on Redis for caching, pub/sub, data structures, and high-performance applications.

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---
name: redis-expert
version: 1.0.0
description: Expert-level Redis for caching, pub/sub, data structures, and high-performance applications
category: data
tags: [redis, cache, pubsub, inmemory, keyvalue, nosql]
allowed-tools:
  - Read
  - Write
  - Edit
  - Bash(redis-cli:*, docker:*)
---

# Redis Expert

Expert guidance for Redis - the in-memory data structure store used as cache, message broker, and database with microsecond latency.

## Core Concepts

### Data Structures
- Strings (binary-safe, up to 512MB)
- Lists (linked lists)
- Sets (unordered unique strings)
- Sorted Sets (sets ordered by score)
- Hashes (field-value pairs)
- Streams (append-only log)
- Bitmaps and HyperLogLog
- Geospatial indexes

### Key Features
- In-memory storage with persistence
- Pub/Sub messaging
- Transactions
- Lua scripting
- Pipelining
- Master-Replica replication
- Redis Sentinel (high availability)
- Redis Cluster (horizontal scaling)

### Use Cases
- Caching layer
- Session storage
- Real-time analytics
- Message queues
- Rate limiting
- Leaderboards
- Geospatial queries

## Installation and Configuration

### Docker Setup
```bash
# Development
docker run --name redis -p 6379:6379 -d redis:7-alpine

# Production with persistence
docker run --name redis \
  -p 6379:6379 \
  -v redis-data:/data \
  -d redis:7-alpine \
  redis-server --appendonly yes --requirepass strongpassword

# Redis with config file
docker run --name redis \
  -p 6379:6379 \
  -v ./redis.conf:/usr/local/etc/redis/redis.conf \
  -d redis:7-alpine \
  redis-server /usr/local/etc/redis/redis.conf
```

### Configuration (redis.conf)
```conf
# Network
bind 0.0.0.0
port 6379
protected-mode yes

# Security
requirepass strongpassword

# Memory
maxmemory 2gb
maxmemory-policy allkeys-lru

# Persistence
save 900 1      # Save after 900s if 1 key changed
save 300 10     # Save after 300s if 10 keys changed
save 60 10000   # Save after 60s if 10000 keys changed

appendonly yes
appendfilename "appendonly.aof"
appendfsync everysec

# Replication
replica-read-only yes
repl-diskless-sync yes

# Performance
tcp-backlog 511
timeout 0
tcp-keepalive 300
```

## Node.js Client (ioredis)

### Basic Operations
```typescript
import Redis from 'ioredis';

const redis = new Redis({
  host: 'localhost',
  port: 6379,
  password: 'strongpassword',
  db: 0,
  retryStrategy: (times) => {
    const delay = Math.min(times * 50, 2000);
    return delay;
  },
});

// Strings
await redis.set('user:1000:name', 'Alice');
await redis.set('counter', 42);
await redis.get('user:1000:name'); // 'Alice'

// Expiration (TTL)
await redis.setex('session:abc123', 3600, JSON.stringify({ userId: 1000 }));
await redis.expire('user:1000:name', 300); // 5 minutes
await redis.ttl('user:1000:name'); // Returns remaining seconds

// Atomic operations
await redis.incr('page:views'); // 1
await redis.incr('page:views'); // 2
await redis.incrby('score', 10); // Increment by 10
await redis.decr('inventory:item123');

// Hashes (objects)
await redis.hset('user:1000', {
  name: 'Alice',
  email: '[email protected]',
  age: 30,
});

await redis.hget('user:1000', 'name'); // 'Alice'
await redis.hgetall('user:1000'); // { name: 'Alice', email: '...', age: '30' }
await redis.hincrby('user:1000', 'loginCount', 1);

// Lists (queues, stacks)
await redis.lpush('queue:jobs', 'job1', 'job2', 'job3'); // Push to left
await redis.rpush('queue:jobs', 'job4'); // Push to right
await redis.lpop('queue:jobs'); // Pop from left (FIFO)
await redis.rpop('queue:jobs'); // Pop from right (LIFO)
await redis.lrange('queue:jobs', 0, -1); // Get all items

// Sets (unique values)
await redis.sadd('tags:post:1', 'javascript', 'nodejs', 'redis');
await redis.smembers('tags:post:1'); // ['javascript', 'nodejs', 'redis']
await redis.sismember('tags:post:1', 'nodejs'); // 1 (true)
await redis.scard('tags:post:1'); // 3 (count)

// Set operations
await redis.sadd('tags:post:2', 'nodejs', 'typescript', 'docker');
await redis.sinter('tags:post:1', 'tags:post:2'); // ['nodejs'] (intersection)
await redis.sunion('tags:post:1', 'tags:post:2'); // All unique tags
await redis.sdiff('tags:post:1', 'tags:post:2'); // ['javascript', 'redis']

// Sorted Sets (leaderboards)
await redis.zadd('leaderboard', 1000, 'player1', 1500, 'player2', 800, 'player3');
await redis.zrange('leaderboard', 0, -1, 'WITHSCORES'); // Ascending
await redis.zrevrange('leaderboard', 0, 9); // Top 10 (descending)
await redis.zincrby('leaderboard', 50, 'player1'); // Add to score
await redis.zrank('leaderboard', 'player1'); // Get rank (0-indexed)
await redis.zscore('leaderboard', 'player1'); // Get score
```

### Advanced Patterns

#### Caching with JSON
```typescript
// Cache helper
class CacheService {
  constructor(private redis: Redis) {}

  async get<T>(key: string): Promise<T | null> {
    const data = await this.redis.get(key);
    return data ? JSON.parse(data) : null;
  }

  async set(key: string, value: any, ttl: number = 3600): Promise<void> {
    await this.redis.setex(key, ttl, JSON.stringify(value));
  }

  async delete(key: string): Promise<void> {
    await this.redis.del(key);
  }

  async getOrSet<T>(
    key: string,
    factory: () => Promise<T>,
    ttl: number = 3600
  ): Promise<T> {
    const cached = await this.get<T>(key);
    if (cached) return cached;

    const fresh = await factory();
    await this.set(key, fresh, ttl);
    return fresh;
  }
}

// Usage
const cache = new CacheService(redis);

const user = await cache.getOrSet(
  'user:1000',
  async () => await db.user.findById(1000),
  3600
);
```

#### Rate Limiting
```typescript
class RateLimiter {
  constructor(private redis: Redis) {}

  async checkRateLimit(
    key: string,
    limit: number,
    window: number
  ): Promise<{ allowed: boolean; remaining: number }> {
    const current = await this.redis.incr(key);

    if (current === 1) {
      await this.redis.expire(key, window);
    }

    return {
      allowed: current <= limit,
      remaining: Math.max(0, limit - current),
    };
  }
}

// Usage: 100 requests per hour per IP
const limiter = new RateLimiter(redis);
const result = await limiter.checkRateLimit(`ratelimit:${ip}`, 100, 3600);

if (!result.allowed) {
  return res.status(429).json({ error: 'Too many requests' });
}
```

#### Sliding Window Rate Limiting
```typescript
async function slidingWindowRateLimit(
  redis: Redis,
  key: string,
  limit: number,
  window: number
): Promise<boolean> {
  const now = Date.now();
  const windowStart = now - window * 1000;

  // Remove old entries
  await redis.zremrangebyscore(key, 0, windowStart);

  // Count requests in window
  const count = await redis.zcard(key);

  if (count < limit) {
    // Add current request
    await redis.zadd(key, now, `${now}-${Math.random()}`);
    await redis.expire(key, window);
    return true;
  }

  return false;
}
```

#### Distributed Locking
```typescript
class RedisLock {
  constructor(private redis: Redis) {}

  async acquire(
    resource: string,
    ttl: number = 10000,
    retryDelay: number = 50,
    retryCount: number = 100
  ): Promise<string | null> {
    const lockKey = `lock:${resource}`;
    const lockValue = crypto.randomUUID();

    for (let i = 0; i < retryCount; i++) {
      const acquired = await this.redis.set(
        lockKey,
        lockValue,
        'PX',
        ttl,
        'NX'
      );

      if (acquired === 'OK') {
        return lockValue;
      }

      await new Promise((resolve) => setTimeout(resolve, retryDelay));
    }

    return null;
  }

  async release(resource: string, lockValue: string): Promise<boolean> {
    const lockKey = `lock:${resource}`;

    // Use Lua script to ensure atomicity
    const script = `
      if redis.call("get", KEYS[1]) == ARGV[1] then
        return redis.call("del", KEYS[1])
      else
        return 0
      end
    `;

    const result = await this.redis.eval(script, 1, lockKey, lockValue);
    return result === 1;
  }

  async withLock<T>(
    resource: string,
    fn: () => Promise<T>,
    ttl: number = 10000
  ): Promise<T> {
    const lockValue = await this.acquire(resource, ttl);
    if (!lockValue) {
      throw new Error('Failed to acquire lock');
    }

    try {
      return await fn();
    } finally {
      await this.release(resource, lockValue);
    }
  }
}

// Usage
const lock = new RedisLock(redis);

await lock.withLock('resource:123', async () => {
  // Critical section - only one process can execute this
  const data = await fetchData();
  await processData(data);
});
```

### Pub/Sub

```typescript
// Publisher
const publisher = new Redis();

await publisher.publish('notifications', JSON.stringify({
  type: 'new_message',
  userId: 1000,
  message: 'Hello!',
}));

// Subscriber
const subscriber = new Redis();

subscriber.subscribe('notifications', (err, count) => {
  console.log(`Subscribed to ${count} channels`);
});

subscriber.on('message', (channel, message) => {
  const data = JSON.parse(message);
  console.log(`Received from ${channel}:`, data);
});

// Pattern subscription
subscriber.psubscribe('user:*:notifications', (err, count) => {
  console.log(`Subscribed to ${count} patterns`);
});

subscriber.on('pmessage', (pattern, channel, message) => {
  console.log(`Pattern ${pattern} matched ${channel}:`, message);
});

// Unsubscribe
await subscriber.unsubscribe('notifications');
await subscriber.punsubscribe('user:*:notifications');
```

### Redis Streams

```typescript
// Add to stream
await redis.xadd(
  'events',
  '*', // Auto-generate ID
  'type', 'user_registered',
  'userId', '1000',
  'email', '[email protected]'
);

// Read from stream
const messages = await redis.xread('COUNT', 10, 'STREAMS', 'events', '0');
/*
[
  ['events', [
    ['1609459200000-0', ['type', 'user_registered', 'userId', '1000']],
    ['1609459201000-0', ['type', 'order_placed', 'orderId', '500']]
  ]]
]
*/

// Consumer Groups
await redis.xgroup('CREATE', 'events', 'worker-group', '0', 'MKSTREAM');

// Read as consumer
const messages = await redis.xreadgroup(
  'GROUP', 'worker-group', 'consumer-1',
  'COUNT', 10,
  'STREAMS', 'events', '>'
);

// Acknowledge message
await redis.xack('events', 'worker-group', '1609459200000-0');

// Pending messages
const pending = await redis.xpending('events', 'worker-group');
```

### Transactions

```typescript
// Multi/Exec (transaction)
const pipeline = redis.multi();
pipeline.set('key1', 'value1');
pipeline.set('key2', 'value2');
pipeline.incr('counter');
const results = await pipeline.exec();

// Watch (optimistic locking)
await redis.watch('balance:1000');
const balance = parseInt(await redis.get('balance:1000') || '0');

if (balance >= amount) {
  const multi = redis.multi();
  multi.decrby('balance:1000', amount);
  multi.incrby('balance:2000', amount);
  await multi.exec(); // Executes only if balance:1000 wasn't modified
} else {
  await redis.unwatch();
}
```

### Pipelining

```typescript
// Pipeline multiple commands
const pipeline = redis.pipeline();
pipeline.set('key1', 'value1');
pipeline.set('key2', 'value2');
pipeline.get('key1');
pipeline.get('key2');
const results = await pipeline.exec();
// [[null, 'OK'], [null, 'OK'], [null, 'value1'], [null, 'value2']]

// Batch operations
async function batchSet(items: Record<string, string>) {
  const pipeline = redis.pipeline();
  for (const [key, value] of Object.entries(items)) {
    pipeline.set(key, value);
  }
  await pipeline.exec();
}
```

### Lua Scripts

```typescript
// Atomic increment with max
const script = `
  local current = redis.call('GET', KEYS[1])
  local max = tonumber(ARGV[1])

  if current and tonumber(current) >= max then
    return tonumber(current)
  else
    return redis.call('INCR', KEYS[1])
  end
`;

const result = await redis.eval(script, 1, 'counter', 100);

// Load script once, execute many times
const sha = await redis.script('LOAD', script);
const result = await redis.evalsha(sha, 1, 'counter', 100);
```

## Redis Cluster

### Setup
```bash
# Create 6 nodes (3 masters, 3 replicas)
for port in {7000..7005}; do
  mkdir -p cluster/${port}
  cat > cluster/${port}/redis.conf <<EOF
port ${port}
cluster-enabled yes
cluster-config-file nodes.conf
cluster-node-timeout 5000
appendonly yes
EOF
  redis-server cluster/${port}/redis.conf &
done

# Create cluster
redis-cli --cluster create \
  127.0.0.1:7000 127.0.0.1:7001 127.0.0.1:7002 \
  127.0.0.1:7003 127.0.0.1:7004 127.0.0.1:7005 \
  --cluster-replicas 1
```

### Cluster Client
```typescript
import Redis from 'ioredis';

const cluster = new Redis.Cluster([
  { host: '127.0.0.1', port: 7000 },
  { host: '127.0.0.1', port: 7001 },
  { host: '127.0.0.1', port: 7002 },
]);

// Operations work transparently
await cluster.set('key', 'value');
await cluster.get('key');
```

## Best Practices

### Memory Management
- Set maxmemory limit
- Choose appropriate eviction policy:
  - `allkeys-lru`: Remove least recently used keys
  - `allkeys-lfu`: Remove least frequently used keys
  - `volatile-lru`: Remove LRU keys with expire set
  - `volatile-ttl`: Remove keys with shortest TTL
- Monitor memory usage: `INFO memory`
- Use memory-efficient data structures

### Key Naming
```typescript
// Good: hierarchical, descriptive
'user:1000:profile'
'session:abc123'
'cache:api:users:page:1'
'ratelimit:ip:192.168.1.1:2024-01-19'

// Use consistent separators
const key = ['user', userId, 'profile'].join(':');
```

### Expiration
- Always set TTL for cache keys
- Use appropriate TTL based on data freshness
- Monitor keys without expiration: `redis-cli --bigkeys`

### Persistence
- Use AOF for durability (appendonly yes)
- Use RDB for backups (save snapshots)
- Test restore procedures

### Monitoring
```bash
# Monitor commands in real-time
redis-cli MONITOR

# Stats
redis-cli INFO

# Slow queries
redis-cli SLOWLOG GET 10

# Memory analysis
redis-cli --bigkeys

# Latency
redis-cli --latency
```

## Performance Optimization

### Connection Pooling
```typescript
const redis = new Redis({
  host: 'localhost',
  port: 6379,
  maxRetriesPerRequest: 3,
  enableReadyCheck: true,
  lazyConnect: true,
});
```

### Avoid KEYS Command
```typescript
// ❌ Bad: Blocks entire server
const keys = await redis.keys('user:*');

// ✅ Good: Use SCAN for large datasets
async function* scanKeys(pattern: string) {
  let cursor = '0';
  do {
    const [newCursor, keys] = await redis.scan(
      cursor,
      'MATCH',
      pattern,
      'COUNT',
      100
    );
    cursor = newCursor;
    yield* keys;
  } while (cursor !== '0');
}

for await (const key of scanKeys('user:*')) {
  console.log(key);
}
```

### Optimize Data Structures
```typescript
// Use hashes for objects instead of multiple keys
// ❌ Bad: 3 keys
await redis.set('user:1000:name', 'Alice');
await redis.set('user:1000:email', '[email protected]');
await redis.set('user:1000:age', '30');

// ✅ Good: 1 key
await redis.hset('user:1000', {
  name: 'Alice',
  email: '[email protected]',
  age: '30',
});
```

## Anti-Patterns to Avoid

❌ **Using Redis as primary database**: Use for caching/sessions
❌ **Not setting TTL on cache keys**: Causes memory bloat
❌ **Using KEYS in production**: Use SCAN instead
❌ **Large values in keys**: Keep values small (<1MB)
❌ **No monitoring**: Track memory, latency, hit rate
❌ **Synchronous blocking operations**: Use async operations
❌ **Not handling connection failures**: Implement retry logic
❌ **Storing large collections in single key**: Split into multiple keys

## Common Use Cases

### Session Store (Express)
```typescript
import session from 'express-session';
import RedisStore from 'connect-redis';

app.use(
  session({
    store: new RedisStore({ client: redis }),
    secret: 'secret',
    resave: false,
    saveUninitialized: false,
    cookie: {
      secure: true,
      httpOnly: true,
      maxAge: 1000 * 60 * 60 * 24, // 24 hours
    },
  })
);
```

### Job Queue (BullMQ)
```typescript
import { Queue, Worker } from 'bullmq';

const queue = new Queue('emails', { connection: redis });

// Add job
await queue.add('send-email', {
  to: '[email protected]',
  subject: 'Welcome',
  body: 'Hello!',
});

// Process jobs
const worker = new Worker('emails', async (job) => {
  await sendEmail(job.data);
}, { connection: redis });
```

## Resources

- Redis Documentation: https://redis.io/docs/
- ioredis: https://github.com/redis/ioredis
- Redis University: https://university.redis.com/
- BullMQ: https://docs.bullmq.io/

Overview

This skill provides expert-level guidance for using Redis as a cache, message broker, and high-performance data store. It covers core data structures, operational best practices, and advanced patterns for reliability and scale. Practical TypeScript examples show common client patterns, distributed locking, streaming, and cluster usage.

How this skill works

The skill inspects Redis features and configuration choices to recommend patterns for caching, pub/sub, streams, transactions, and clustering. It explains how to use ioredis from Node.js with concrete code for strings, hashes, lists, sets, sorted sets, streams, pipelining, Lua scripts, and transactions. It also recommends operational settings for memory, persistence, replication, and high availability.

When to use it

  • Add a low-latency caching layer to reduce DB load and speed up reads
  • Implement real-time messaging or pub/sub notifications between services
  • Build durable, ordered event streams and consumer groups for background processing
  • Enforce rate limits and sliding-window quotas for APIs
  • Use lightweight distributed locks for critical sections across processes

Best practices

  • Set maxmemory and a clear eviction policy (allkeys-lru/lfu or volatile variants) and monitor with INFO memory
  • Use hierarchical key naming (e.g., user:1000:profile) and consistent separators for discoverability
  • Always set TTLs for cache keys; avoid long-lived keys unless intentional
  • Prefer SCAN over KEYS for large datasets and use pipelining for batch operations
  • Use AOF for durability and test restore procedures; enable replication and Sentinel/Cluster for HA

Example use cases

  • Cache API responses with JSON helpers and getOrSet pattern to prevent thundering herd
  • Implement per-IP rate limiting using incr + expire or sliding-window with sorted sets
  • Create leaderboards using sorted sets and efficient rank/score queries
  • Process events with Redis Streams, consumer groups, xack, and pending inspection
  • Coordinate distributed tasks with a Redis-based lock (SET NX PX + Lua release)

FAQ

When should I choose Redis Cluster vs single instance with replicas?

Use Cluster when you need horizontal scaling and sharding for dataset size or throughput. Single instance with replicas suits smaller datasets with simpler failover via Sentinel.

How do I avoid race conditions when updating shared counters or balances?

Use WATCH + MULTI for optimistic transactions or Lua scripts for atomic server-side logic. For cross-process critical sections, use a robust locking pattern with unique tokens and Lua-based release.