Pod Autoscalers in Kubernetes

Kubernetes provides autoscaling mechanisms to dynamically adjust the number of running Pods based on real-time workload demands. This ensures efficient use of cluster resources while maintaining application performance and availability.

There are two primary autoscalers in Kubernetes:

1. Horizontal Pod Autoscaler (HPA): Adjusts the number of Pod replicas based on metrics like CPU usage, memory, or custom metrics.
2. Vertical Pod Autoscaler (VPA): Adjusts the CPU and memory resource requests for individual Pods based on historical usage patterns.
3. Cluster Autoscaler: Scales the number of nodes in the cluster, ensuring that there are enough resources for Pods when the cluster is under pressure.

This guide focuses on Pod autoscalers: HPA and VPA.

Section 1: Horizontal Pod Autoscaler (HPA)

The Horizontal Pod Autoscaler (HPA) adjusts the number of Pod replicas in a Deployment, ReplicaSet, or StatefulSet based on observed CPU utilization, memory usage, or custom metrics. It is particularly useful for scaling applications up and down automatically based on workload traffic or demand.

Key Concepts:

• Target Metric: The resource (e.g., CPU, memory) or custom metric to…