---
title: "Scaling"
description: "Scaling strategies for TraceRTM"
keywords: [scaling, scale, horizontal, vertical, performance]
---

# Scaling

Scaling strategies to handle increased load in TraceRTM.

## Scaling Types

### Horizontal Scaling

Add more instances:

```yaml
# Kubernetes
replicas: 3 → 10
```

**Benefits:**
- No downtime
- Better fault tolerance
- Cost-effective

### Vertical Scaling

Increase resources:

```yaml
resources:
  memory: "2Gi" → "4Gi"
  cpu: "2000m" → "4000m"
```

**Benefits:**
- Simple
- No code changes

## Scaling Components

### Application Scaling

```yaml
# Auto-scale API pods
apiVersion: autoscaling/v2
kind: HorizontalPodAutoscaler
spec:
  minReplicas: 3
  maxReplicas: 10
  metrics:
  - type: Resource
    resource:
      name: cpu
      target:
        averageUtilization: 70
```

### Database Scaling

#### Read Replicas

```python
# Route reads to replicas
read_db = create_engine(READ_REPLICA_URL)
write_db = create_engine(WRITE_DB_URL)
```

#### Connection Pooling

```python
engine = create_engine(
    DATABASE_URL,
    pool_size=20,
    max_overflow=10
)
```

### Cache Scaling

```yaml
# Redis cluster
redis:
  replicas: 3
  shards: 3
```

## Auto-Scaling

### Kubernetes HPA

```yaml
apiVersion: autoscaling/v2
kind: HorizontalPodAutoscaler
metadata:
  name: tracertm-api-hpa
spec:
  scaleTargetRef:
    apiVersion: apps/v1
    kind: Deployment
    name: tracertm-api
  minReplicas: 3
  maxReplicas: 10
  metrics:
  - type: Resource
    resource:
      name: cpu
      target:
        type: Utilization
        averageUtilization: 70
```

## Scaling Checklist

- [ ] Stateless services
- [ ] Load balancing configured
- [ ] Database connection pooling
- [ ] Caching layer
- [ ] Monitoring and alerts
- [ ] Auto-scaling configured

## Related Documentation

- [Horizontal Scaling](./06a-horizontal-scaling) - Horizontal scaling
- [Load Balancing](./06b-load-balancing) - Load balancer setup
- [Scalability](../../01-architecture/06b-scalability) - Architecture scalability
