Scalability

Learn how to scale Query-2jz for large applications and high-traffic scenarios.

What is Scalability?

Query-2jz is designed to scale horizontally and vertically, handling millions of requests and petabytes of data with automatic load balancing and intelligent resource management.

Scalability Features

Horizontal scaling

Load balancing

Database sharding

Auto-scaling

Connection pooling

Performance monitoring

Horizontal Scaling

Scale your Query-2jz application across multiple instances and regions.

Multi-Instance Deployment

Deploy Query-2jz across multiple instances

Load Balancer Configuration

# nginx.conf
upstream query-2jz_backend {
    least_conn;
    server query-2jz-1:3000 weight=3;
    server query-2jz-2:3000 weight=3;
    server query-2jz-3:3000 weight=2;
    keepalive 32;
}

server {
    listen 80;
    server_name api.example.com;
    
    location / {
        proxy_pass http://query-2jz_backend;
        proxy_http_version 1.1;
        proxy_set_header Upgrade $http_upgrade;
        proxy_set_header Connection 'upgrade';
        proxy_set_header Host $host;
        proxy_set_header X-Real-IP $remote_addr;
        proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;
        proxy_set_header X-Forwarded-Proto $scheme;
        proxy_cache_bypass $http_upgrade;
    }
}

Docker Compose

version: '3.8'
services:
  query-2jz-1:
    image: query-2jz:latest
    environment:
      - NODE_ENV=production
      - DATABASE_URL=postgresql://user:pass@db:5432/query-2jz
      - REDIS_URL=redis://redis:6379
      - INSTANCE_ID=query-2jz-1
    ports:
      - "3001:3000"
    depends_on:
      - db
      - redis

  query-2jz-2:
    image: query-2jz:latest
    environment:
      - NODE_ENV=production
      - DATABASE_URL=postgresql://user:pass@db:5432/query-2jz
      - REDIS_URL=redis://redis:6379
      - INSTANCE_ID=query-2jz-2
    ports:
      - "3002:3000"
    depends_on:
      - db
      - redis

  query-2jz-3:
    image: query-2jz:latest
    environment:
      - NODE_ENV=production
      - DATABASE_URL=postgresql://user:pass@db:5432/query-2jz
      - REDIS_URL=redis://redis:6379
      - INSTANCE_ID=query-2jz-3
    ports:
      - "3003:3000"
    depends_on:
      - db
      - redis

  nginx:
    image: nginx:alpine
    ports:
      - "80:80"
    volumes:
      - ./nginx.conf:/etc/nginx/nginx.conf
    depends_on:
      - query-2jz-1
      - query-2jz-2
      - query-2jz-3

Database Sharding

Distribute your data across multiple database instances for better performance.

Sharding Configuration

Configure database sharding for large datasets

Sharding Strategy

{
  "database": {
    "type": "postgresql",
    "sharding": {
      "enabled": true,
      "strategy": "hash",
      "shards": [
        {
          "id": "shard-1",
          "connection": "postgresql://user:pass@shard1:5432/query-2jz",
          "weight": 1
        },
        {
          "id": "shard-2", 
          "connection": "postgresql://user:pass@shard2:5432/query-2jz",
          "weight": 1
        },
        {
          "id": "shard-3",
          "connection": "postgresql://user:pass@shard3:5432/query-2jz",
          "weight": 1
        }
      ],
      "shardKey": "id",
      "replication": {
        "enabled": true,
        "factor": 2
      }
    }
  }
}

Shard Selection

// Automatic shard selection
const user = await query-2jz.query({
  model: 'User',
  where: { id: 'user-123' }
});
// Automatically routes to correct shard

// Cross-shard queries
const users = await query-2jz.query({
  model: 'User',
  where: { status: 'active' }
});
// Automatically queries all shards and merges results

// Shard-aware operations
const result = await query-2jz.create({
  model: 'User',
  data: { name: 'John Doe', email: 'john@example.com' }
});
// Automatically selects shard based on shard key

Auto-Scaling

Automatically scale your Query-2jz instances based on demand.

Auto-Scaling Configuration

Configure automatic scaling based on metrics

Kubernetes HPA

apiVersion: autoscaling/v2
kind: HorizontalPodAutoscaler
metadata:
  name: query-2jz-hpa
spec:
  scaleTargetRef:
    apiVersion: apps/v1
    kind: Deployment
    name: query-2jz
  minReplicas: 3
  maxReplicas: 20
  metrics:
  - type: Resource
    resource:
      name: cpu
      target:
        type: Utilization
        averageUtilization: 70
  - type: Resource
    resource:
      name: memory
      target:
        type: Utilization
        averageUtilization: 80
  - type: Pods
    pods:
      metric:
        name: query-2jz_requests_per_second
      target:
        type: AverageValue
        averageValue: "100"

Custom Metrics

// Custom scaling metrics
{
  "scaling": {
    "enabled": true,
    "metrics": [
      {
        "name": "request_rate",
        "threshold": 1000,
        "action": "scale_up"
      },
      {
        "name": "response_time",
        "threshold": 500,
        "action": "scale_up"
      },
      {
        "name": "cpu_usage",
        "threshold": 80,
        "action": "scale_up"
      },
      {
        "name": "memory_usage",
        "threshold": 85,
        "action": "scale_up"
      }
    ],
    "cooldown": 300,  // 5 minutes
    "minInstances": 2,
    "maxInstances": 50
  }
}

Connection Pooling

Optimize database connections for high concurrency.

Advanced Pool Configuration

{
  "database": {
    "type": "postgresql",
    "connection": "postgresql://user:pass@localhost:5432/query-2jz",
    "pool": {
      "min": 5,                    // Minimum connections
      "max": 100,                  // Maximum connections
      "idleTimeoutMillis": 30000,  // Idle timeout
      "connectionTimeoutMillis": 2000,  // Connection timeout
      "acquireTimeoutMillis": 60000,    // Acquire timeout
      "createTimeoutMillis": 30000,     // Create timeout
      "destroyTimeoutMillis": 5000,     // Destroy timeout
      "reapIntervalMillis": 1000,       // Reap interval
      "createRetryIntervalMillis": 200, // Retry interval
      "propagateCreateError": false     // Propagate create error
    },
    "cluster": {
      "enabled": true,
      "nodes": [
        "postgresql://user:pass@db1:5432/query-2jz",
        "postgresql://user:pass@db2:5432/query-2jz",
        "postgresql://user:pass@db3:5432/query-2jz"
      ],
      "loadBalance": "round_robin"
    }
  }
}

Pool Monitoring

// Monitor connection pools
const poolStats = await query-2jz.getPoolStats();

console.log({
  totalConnections: poolStats.total,
  activeConnections: poolStats.active,
  idleConnections: poolStats.idle,
  waitingClients: poolStats.waiting,
  averageAcquireTime: poolStats.averageAcquireTime,
  averageReleaseTime: poolStats.averageReleaseTime
});

// Pool events
query-2jz.on('pool:connection', (connection) => {
  console.log('New connection created');
});

query-2jz.on('pool:acquire', (connection) => {
  console.log('Connection acquired');
});

query-2jz.on('pool:release', (connection) => {
  console.log('Connection released');
});

query-2jz.on('pool:error', (error) => {
  console.error('Pool error:', error);
});

Performance Monitoring

Monitor and analyze performance across your scaled infrastructure.

Monitoring Dashboard

Comprehensive performance monitoring

Key Metrics

System Metrics

• CPU usage per instance
• Memory usage per instance
• Network I/O
• Disk I/O
• Load average

Application Metrics

• Request rate
• Response time
• Error rate
• Active connections
• Cache hit rate

Monitoring Configuration

{
  "monitoring": {
    "enabled": true,
    "metrics": {
      "system": ["cpu", "memory", "network", "disk"],
      "application": ["requests", "response_time", "errors", "connections"],
      "database": ["queries", "connections", "transactions"],
      "cache": ["hit_rate", "miss_rate", "evictions"]
    },
    "alerts": {
      "cpu_usage": { "threshold": 80, "duration": "5m" },
      "memory_usage": { "threshold": 85, "duration": "5m" },
      "response_time": { "threshold": 1000, "duration": "2m" },
      "error_rate": { "threshold": 5, "duration": "1m" }
    },
    "exporters": ["prometheus", "grafana", "datadog"]
  }
}

Scaling Strategies

Different approaches to scaling your Query-2jz application.

Vertical Scaling

Scale up individual instances

• Increase CPU cores
• Add more RAM
• Upgrade storage
• Faster network
• Better hardware

Horizontal Scaling

Scale out with more instances

• Add more instances
• Load balancing
• Database sharding
• Microservices
• Container orchestration

Best Practices

Do

• Plan for horizontal scaling
• Use load balancers
• Implement proper monitoring
• Use connection pooling
• Optimize database queries
• Implement caching strategies
• Use auto-scaling

Don't

• Ignore performance bottlenecks
• Skip load testing
• Forget to monitor metrics
• Use inefficient queries
• Ignore connection limits
• Skip error handling
• Ignore capacity planning