system-prompts-and-models-of-ai-tools/claude_skills/backend-scaling/SKILL.md

name	description	allowed-tools
backend-scaling	Expert in backend scaling strategies including load balancing, caching, database sharding, microservices, and horizontal/vertical scaling. Use when optimizing for high traffic, designing scalable architectures, or troubleshooting performance under load.	Read, Write, Edit, Grep, Glob, Bash

Backend Scaling Expert

Purpose

Design and implement scalable backend systems handling high traffic and large datasets.

Strategies

• Horizontal scaling: Add more servers
• Vertical scaling: Increase server resources
• Load balancing: Distribute traffic (Nginx, HAProxy, ALB)
• Caching layers: Redis, Memcached, CDN
• Database sharding: Split data across databases
• Read replicas: Separate read and write operations
• Microservices: Decompose monoliths
• Message queues: Async processing (RabbitMQ, Kafka)
• Connection pooling: Reuse database connections
• Rate limiting: Prevent abuse

Architecture Patterns

// Load balancer configuration (Nginx)
upstream backend {
  least_conn;
  server backend1.example.com weight=3;
  server backend2.example.com weight=2;
  server backend3.example.com backup;
}

// Rate limiting middleware
import rateLimit from 'express-rate-limit';

const limiter = rateLimit({
  windowMs: 15 * 60 * 1000,
  max: 100,
  standardHeaders: true,
  legacyHeaders: false,
});

app.use('/api/', limiter);

// Database sharding strategy
class ShardedDB {
  getShardForUser(userId: string): Database {
    const shardId = hashFunction(userId) % NUM_SHARDS;
    return this.shards[shardId];
  }

  async getUserData(userId: string) {
    const shard = this.getShardForUser(userId);
    return shard.query('SELECT * FROM users WHERE id = ?', [userId]);
  }
}

// Message queue for async processing
import { Queue } from 'bullmq';

const emailQueue = new Queue('emails', {
  connection: { host: 'redis', port: 6379 }
});

// Add job
await emailQueue.add('welcome-email', {
  to: 'user@example.com',
  template: 'welcome'
});

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

Success Criteria

• ✓ Handle 10,000+ req/sec
• ✓ <100ms p99 latency
• ✓ 99.9% uptime
• ✓ Auto-scaling configured
• ✓ Zero single points of failure