Kubernetes Autoscaling: Load Got Bigger, So Did We!

Load Got Bigger, So Did We!

🚀 Intro

Today, I faced a simple yet real question — what if our pods can’t handle user traffic? 📈

That led me to understand Kubernetes Autoscaling — a powerful mechanism that ensures your application survives sudden spikes.

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🔄 Horizontal Pod Autoscaler (HPA)

• It scales out/in your pod count based on resource metrics.

• Achieved via kubectl autoscale or YAML object

• Demo: We created an Apache server and simulated traffic to see how pod replicas increase 🔄

📈 Vertical Pod Autoscaler (VPA)

• Instead of adding pods, it resizes existing ones (scale up/down).

• Best when single pods need more horsepower.

⚡ KEDA (Event Driven Autoscaling)

• Triggers scaling on events like queue size, cron jobs, or custom metrics.

• Ideal for production-grade workflows.

🔍 My Learnings

• Debugging autoscaling felt tricky but rewarding.

• Watching kubectl get hpa --watch respond in real time felt magical 🤖

• Differentiating workload vs infrastructure scaling was a game-changer.