LEARNK8S LAB SERIES: How to (right) size your Kubernetes cluster for efficiency

In Kubernetes, should you use fewer large nodes or several smaller ones?

When using an 8 GB/2vCPU instance, are all the memory and CPU available to pods?

In this session, you will explore how Kubernetes reserves resources in a worker node. You will learn how different cloud providers have different reservations and how those affect deploying workloads and their availability. You’ll then examine how limits, requests and reservations can be combined to estimate the right instance size for your Kubernetes workloads.

By the end of the session, you will:

  • Understand how the Kubernetes scheduler uses requests to allocate workloads.
  • Identify how the kubelet reserves CPU, memory, storage, etc., in a Kubernetes node.
  • Master how to choose the right size for your cluster nodes to optimize resource utilization for your workload.

If you couldn’t make it, register via the link above and we’ll send you the on-demand recording.