Docs / Kubernetes & Orchestration / Kubernetes Horizontal Pod Autoscaling

Kubernetes Horizontal Pod Autoscaling

By Admin · Feb 4, 2026 · Updated Apr 25, 2026 · 7 views · 3 min read

In this article, we'll walk through the complete process of working with hpa in a server environment. Understanding autoscaling is essential for maintaining a reliable and performant infrastructure.

Prerequisites

  • A VPS running Ubuntu 22.04 or later (2GB+ RAM recommended)
  • kubectl installed on your local machine
  • Root or sudo access to the server

Deploying the Application

The hpa configuration requires careful attention to resource limits and security settings. On a VPS with limited resources, it's important to tune these parameters according to your available RAM and CPU cores.


# deployment.yaml
apiVersion: apps/v1
kind: Deployment
metadata:
  name: hpa-app
  labels:
    app: hpa
spec:
  replicas: 2
  selector:
    matchLabels:
      app: hpa
  template:
    metadata:
      labels:
        app: hpa
    spec:
      containers:
      - name: hpa
        image: hpa:latest
        ports:
        - containerPort: 8080
        resources:
          requests:
            memory: "128Mi"
            cpu: "250m"
          limits:
            memory: "256Mi"
            cpu: "500m"

The output should show the service running without errors. If you see any warning messages, address them before proceeding to the next step.

  • Keep your system packages updated regularly
  • Monitor disk space usage and set up alerts
  • Review log files weekly for anomalies
  • Enable automatic security updates for critical patches

Configuring Services and Ingress

Before making changes to the configuration, always create a backup of the existing files. This ensures you can quickly roll back if something goes wrong during the setup process.


# Apply the configuration
kubectl apply -f deployment.yaml
kubectl apply -f service.yaml

# Verify the deployment
kubectl get pods -l app=hpa
kubectl describe deployment hpa-app
kubectl logs -f deployment/hpa-app

Make sure to restart the service after applying these changes. Some settings require a full restart rather than a reload to take effect.

Configuration Options

Performance benchmarks show that properly tuned hpa can handle significantly more concurrent connections than the default configuration. The key improvements come from adjusting worker processes and connection pooling.

Setting Up Persistent Storage

The autoscaling component plays a crucial role in the overall architecture. Understanding how it interacts with hpa will help you make better configuration decisions.


# service.yaml
apiVersion: v1
kind: Service
metadata:
  name: hpa-service
spec:
  selector:
    app: hpa
  ports:
  - port: 80
    targetPort: 8080
  type: ClusterIP

Each line in the configuration serves a specific purpose. The comments explain the reasoning behind each setting, making it easier to customize for your specific use case.

Wrapping Up

Following this guide, your hpa setup should be production-ready. Keep an eye on resource usage as your traffic grows and don't forget to test your backup and recovery procedures periodically.

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