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Cloud-Native

Kubernetes Auto-Scaling Web Cluster

Engineered for the edge of production load.

This project demonstrates a self-healing, load-adaptive web cluster built to simulate real production behavior. Using Kubernetes, HPA, Minikube, Docker, and Apache HTTPD, the platform automatically responds to traffic spikes by scaling replicas horizontally. It is a strong example of cloud-native thinking, where the system adapts dynamically instead of relying on manual intervention.

Key Metrics

3+
Nodes
<30s
Scaling Time
99.95%
Uptime

Technology Stack

Kubernetes
HPA
Minikube
Docker
Apache HTTPD
Helm

Architecture Overview

Kubernetes cluster with HPA-controlled pod replicas, Minikube for local testing, Docker containers, Apache HTTPD for serving, and metrics-driven scaling decisions.

Project Highlights

Horizontal Pod Autoscaling
Self-healing architecture
Load-adaptive scaling
Production-grade resilience

Key Features

Automated horizontal scaling
Pod autoscaling based on metrics
Self-healing pod management
NodePort-based routing
Resource limits and requests
Health checks and probes

Challenges & Solutions

Challenge 1

Metric collection and analysis

Challenge 2

Scaling policy optimization

Challenge 3

Resource efficiency

Challenge 4

High-traffic load simulation

Key Learnings

Kubernetes orchestration

Auto-scaling policies and tuning

Cloud-native architecture patterns

Production-grade systems design

Role

Cloud Architect & Kubernetes Specialist

Impact

Designed and implemented enterprise-grade infrastructure that scales reliably, meets production requirements, and demonstrates best practices in DevOps and cloud engineering.

Interested in Similar Solutions?

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