Scaling Strategies

Stratégies de scaling pour Genesis AI.

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📊 Types de Scaling

1. Horizontal Scaling

Ajouter plus d'instances.

# Kubernetes HPA
apiVersion: autoscaling/v2
kind: HorizontalPodAutoscaler
metadata:
  name: nexus-hpa
spec:
  scaleTargetRef:
    apiVersion: apps/v1
    kind: Deployment
    name: genesis-nexus
  minReplicas: 3
  maxReplicas: 20
  metrics:
  - type: Resource
    resource:
      name: cpu
      target:
        type: Utilization
        averageUtilization: 70

2. Vertical Scaling

Augmenter les ressources par instance.

# Kubernetes resources
resources:
  requests:
    cpu: 500m
    memory: 512Mi
  limits:
    cpu: 2000m
    memory: 2Gi

3. Auto-scaling

Scaling automatique basé sur la charge.

# KEDA (Kubernetes Event-driven Autoscaling)
triggers:
- type: prometheus
  metadata:
    serverAddress: http://prometheus:9090
    metricName: igon7_queue_size
    threshold: '100'

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🔄 Load Balancing

Stratégies

Stratégie	Description	Use Case
Round Robin	Distribution égale	Charge uniforme
Least Connections	Moins de connexions	Long-running tasks
IP Hash	Sticky sessions	Sessions persistantes
Weighted	Poids par instance	Instances hétérogènes

Configuration Nginx

upstream genesis {
    least_conn;
    server nexus-1:8080 weight=3;
    server nexus-2:8080 weight=2;
    server nexus-3:8080 weight=1;
}

server {
    location / {
        proxy_pass http://genesis;
    }
}

---

📈 Database Scaling

Read Replicas

# PostgreSQL avec replicas
primary:
  resources:
    cpu: 2000m
    memory: 4Gi
  
replicas: 3
read_only: true

Sharding

// Sharding par user_id
const shard = user_id % num_shards;
const db = databases[shard];

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🚀 Performance Tuning

Nexus

// Configuration optimisée
const nexusConfig = {
  maxConcurrentAgents: 100,
  maxConnections: 10000,
  requestTimeout: 30000,
  heartbeatInterval: 30000,
};

igon7

// Configuration optimisée
const igon7Config = {
  maxConcurrentWorkflows: 100,
  maxConcurrentNodesPerWorkflow: 50,
  defaultTimeout: 300000,
};

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✅ Monitoring

Métriques clés

• CPU Usage : < 70%
• Memory Usage : < 80%
• Queue Size : < 1000
• Response Time : P95 < 500ms
• Error Rate : < 1%

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Version : 1.0.0
Niveau : Avancé