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Introduction to Autoscaling 2025 Updates

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Introduction to Autoscaling 2025 Updates

Source: https://notes.kodekloud.com/docs/CKA-Certification-Course-Certified-Kubernetes-Administrator/Application-Lifecycle-Management/Introduction-to-Autoscaling-2025-Updates/page

Summary: This article explores autoscaling in Kubernetes, focusing on Horizontal and Vertical Pod Autoscaling for the Certified Kubernetes Administrator exam.

Key Notes

  • Kubernetes Autoscaling course on KodeKloud
  • Before diving into autoscaling in Kubernetes, let’s review the traditional concepts of scaling using physical servers.
  • Imagine a past scenario where applications were deployed on physical servers with fixed CPU and memory capacities. When the application load exceeded server capacity, you had two options:
  • Shut down the application and upgrade the existing server by adding more CPU and memory (vertical scaling).
  • If the application could run multiple instances, add another server to distribute the load without downtime (horizontal scaling).
  • Vertical scaling means enhancing a single server’s resources, whereas horizontal scaling means incorporating additional servers to manage increased load.
  • Now, let’s see how these concepts apply to Kubernetes and containerized environments. Kubernetes is designed to dynamically scale containerized applications. Two primary scaling strategies in Kubernetes are:
  • Scaling workloads – adding or removing containers (Pods) in the cluster.
  • Scaling the underlying cluster infrastructure – adding or removing nodes (servers) in the cluster.
  • To clarify:
  • For the cluster infrastructure:
  • Horizontal scaling:
  • Vertical scaling:
  • For workloads:
  • There are two approaches to scaling in Kubernetes: manual and automated.
  • Manual scaling and automated scaling both have their place. Manual scaling involves direct intervention and command execution, while automated scaling leverages Kubernetes controllers for dynamic adjustments.
  • Manual Scaling
  • For manual scaling, use the following methods:
  • Cluster Infrastructure Horizontal Scaling:
  • Workload Horizontal Scaling:
  • —replicas=
  • <
  • Workload Vertical Scaling:

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