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Scaling

OPS Advanced

Scale EZ-Console applications horizontally and vertically.

Overview​

This guide covers scaling strategies for EZ-Console applications, including horizontal scaling, vertical scaling, database scaling, and load balancing.

Scaling Strategies​

Horizontal Scaling​

Add more application instances to handle increased load.

Vertical Scaling​

Increase resources (CPU, memory) of existing instances.

Application Scaling​

Horizontal Scaling​

Docker Compose​

version: '3.8'

services:
  app:
    build: .
    deploy:
      replicas: 3
    environment:
      - DATABASE_HOST=db

Kubernetes​

apiVersion: apps/v1
kind: Deployment
metadata:
  name: myapp
spec:
  replicas: 5  # Scale to 5 instances
  selector:
    matchLabels:
      app: myapp
  template:
    # ...

Auto Scaling​

apiVersion: autoscaling/v2
kind: HorizontalPodAutoscaler
metadata:
  name: myapp-hpa
spec:
  scaleTargetRef:
    apiVersion: apps/v1
    kind: Deployment
    name: myapp
  minReplicas: 2
  maxReplicas: 10
  metrics:
  - type: Resource
    resource:
      name: cpu
      target:
        type: Utilization
        averageUtilization: 70

Vertical Scaling​

Increase container resources:

resources:
  requests:
    memory: "512Mi"
    cpu: "500m"
  limits:
    memory: "1Gi"
    cpu: "1000m"

Database Scaling​

Read Replicas​

Use read replicas for read-heavy workloads:

database:
  driver: "mysql"
  host: "db-primary.example.com"  # Write to primary
  read_replicas:
    - host: "db-replica-1.example.com"
    - host: "db-replica-2.example.com"

Connection Pooling​

Optimize connection pool settings:

database:
  max_open_connections: 200
  max_idle_connections: 20
  max_connection_life_time: "5m"

Database Sharding​

For very large databases, consider sharding:

  • Shard by organization ID
  • Shard by date range
  • Use consistent hashing

Load Balancing​

Application Load Balancer​

Nginx​

upstream myapp {
    least_conn;
    server app1:8080;
    server app2:8080;
    server app3:8080;
}

server {
    location /api {
        proxy_pass http://myapp;
        proxy_set_header Host $host;
        proxy_set_header X-Real-IP $remote_addr;
    }
}

HAProxy​

backend myapp
    balance roundrobin
    server app1 app1:8080 check
    server app2 app2:8080 check
    server app3 app3:8080 check

Session Affinity​

For stateful applications:

upstream myapp {
    ip_hash;  # Sticky sessions
    server app1:8080;
    server app2:8080;
}

Caching​

Application Cache​

// Use in-memory cache
cache.Set(key, value, 5*time.Minute)

// Use Redis for distributed cache
redis.Set(ctx, key, value, 5*time.Minute)

Database Query Cache​

Enable query caching:

database:
  enable_query_cache: true
  query_cache_size: 100MB

CDN for Static Assets​

Serve static files from CDN:

location /static {
    proxy_pass https://cdn.example.com;
}

Performance Optimization​

Database Indexes​

Add indexes for frequently queried fields:

type Product struct {
    Name     string `gorm:"index"`
    Category string `gorm:"index"`
    Status   string `gorm:"index"`
}

Query Optimization​

// Use Select to limit fields
db.Select("id", "name").Find(&products)

// Use pagination
db.Offset(offset).Limit(limit).Find(&products)

// Use preloading
db.Preload("Category").Find(&products)

Connection Pooling​

database:
  max_open_connections: 200
  max_idle_connections: 20

Monitoring Scaling​

Metrics to Monitor​

  • CPU Usage: Should stay below 70%
  • Memory Usage: Monitor for leaks
  • Request Rate: Requests per second
  • Response Time: P50, P95, P99
  • Error Rate: Should be < 1%

Prometheus Queries​

# CPU usage
rate(container_cpu_usage_seconds_total[5m])

# Memory usage
container_memory_usage_bytes

# Request rate
rate(http_requests_total[5m])

# Error rate
rate(http_requests_total{status=~"5.."}[5m])

Scaling Checklist​

  • Monitor application metrics
  • Set up auto-scaling
  • Configure load balancer
  • Optimize database queries
  • Add caching layer
  • Use CDN for static assets
  • Test under load
  • Document scaling procedures

Need help? Ask in GitHub Discussions.