> ## Documentation Index
> Fetch the complete documentation index at: https://docs.apinizer.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Automatic Scaling of Apinizer Environments

> You can configure horizontal scaling operations for pods, automatically increase and decrease the number of pods according to application demands, and optimize resource usage.

This document explains how to configure **horizontal auto-scaling** operations for pods.

This horizontal scaling feature optimizes resource usage by automatically increasing and decreasing the number of pods according to application demands.

To use the scaling feature in your Kubernetes cluster, a metric-server must be installed. If it is not available, you can check the [Kubernetes Metric Server Installation](/en/setup/kubernetes/kubernetes-metric-server) page for installation.

```bash theme={null}
sudo vi hpa-autoscaling.yaml
```

Edit the NAMESPACE and DEPLOYMENT\_NAME fields in the Yaml according to your application.

```yaml theme={null}
apiVersion: autoscaling/v2
kind: HorizontalPodAutoscaler
metadata:
  name: apinizer-hpa
  namespace: <NAMESPACE>
spec:
  scaleTargetRef:
    apiVersion: apps/v1
    kind: Deployment
    name: <DEPLOYMENT_NAME>
  minReplicas: 1
  maxReplicas: 10
  metrics:
  - type: Resource
    resource:
      name: cpu
      target:
        type: Utilization
        averageUtilization: 70
  - type: Resource
    resource:
      name: memory
      target:
        type: Utilization
        averageUtilization: 70
  behavior:
    scaleDown:
      selectPolicy: Max
      policies:
      - type: Pods
        value: 1
        periodSeconds: 60
    scaleUp:
      stabilizationWindowSeconds: 60
      policies:
      - type: Pods
        value: 1
        periodSeconds: 60
      selectPolicy: Max
```

```bash theme={null}
kubectl apply -f manager-hpa-autoscaling.yaml
```

| Field              | Description                                                                                                                                                                                                    |
| ------------------ | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| scaleTargetRef     | This field specifies which deployment the scaling will work for. Example: manager.                                                                                                                             |
| minReplicas        | Minimum number of pods that should exist. Example: 2.                                                                                                                                                          |
| maxReplicas        | Maximum number of pods that can exist in the system. Example: 10.                                                                                                                                              |
| averageUtilization | In this field, you can enter a percentage value for cpu and memory usage. It will create pods when it exceeds the specified level.                                                                             |
| scaleDown          | When it falls below the target usage level, it will reduce pods by the given value amount every 60 seconds from the newly created pods.                                                                        |
| scaleUp            | When it exceeds the target usage level, it is checked for 60 seconds, which is the **stabilizationWindowSeconds** value specified. If the condition is met, one pod is added to your cluster every 60 seconds. |

<Info>
  To disable the scaleDown feature, change it to **"selectPolicy: Disabled"**.
</Info>