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Autoscaling EKS Node Groups with Karpenter

Managing autoscaling of nodes in an EKS cluster via Karpenter.

Posted by Anadi Misra on September 17, 2023 · 6 mins read

Karpenter is an open-source tool for automating node provisioning in Kubernetes. Karpenter aims to enhance both the effectiveness and affordability of managing workloads within a Kubernetes cluster. The core mechanics of Karpenter involve:

  • Monitoring unschedulable pods identified by the Kubernetes scheduler.
  • Scrutinizing the scheduling constraints, including resource requests, node selectors, affinities, tolerations, and topology spread constraints, as stipulated by the pods.
  • Provisioning nodes that precisely align with the pods’ requirements.
  • Streamlining cluster resource usage by removing nodes once their services are no longer required.

Why we moved to Karpenter?

We at NimbleWork used AWS Fargate in the past for running on-demand, short-lived or one-off workloads, one of the examples being running Jenkins slaves in AWS Fargate while the Master runs on worker nodes. Fargate is good in the sense that it takes care of managing node infrastructure, but can cost premium if you’re using it for long running workloads. It is for this reason that EKS deployment with Worker Nodes is the more preferred path. But with that comes a new problem, unlike Fargate, we have to not just manage creating nodes and node groups, we also have to ensure that our EC2 nodes utilisation is optimal. It comes back to hurt us specially when we realise there’s an entire VM running on just 10% of the CPU/Mem capacity because it has two active pods, which we could have moved to another node and claimed this one. In the past we’ve relied on a cocktail of Prometheus Alerts and Fluent-Bit monitoring data to conclude we can reschedule pods and clean-up un-used nodes. But any self-respecting Engineering Manager would tell you they’d jump to a better alternative than this as soon as they find one. For us Karpenter came as that alternative.

How it works?

Karpenter allows you to define Provisioners which are the heart of it’s cluster management capability. When initially installing Karpenter, you establish a default Provisioner, which imparts specific constraints on the nodes created by Karpenter and the pods eligible to run on these nodes. These constraints encompass defining taints to restrict pod deployment on Karpenter-created nodes, establishing startup taints to indicate temporary node tainting, narrowing down node creation to preferred zones, instance types, and computer architectures, and configuring default settings for node expiration. The Provisioner, in essence, empowers you with fine-grained control over resource allocation within your Kubernetes cluster. You can read up more on Provisioners here.

Deploying EKS Cluster

Here’s how to deploy the EKS cluster with Karpenter.

Setting Up the VPC

Before we begin, let’s deploy the AWS VPC to run our EKS cluster. we’ll be using terraform for provisioning on the AWS Cloud.

We’re using the community contributed modules here for spinning up a VPC which has public and private subnets, and ingress rules. For those interested in more details here a simple example of what could potentially go in the ingress rules

The "" = "mycluster" tag in the vpc module and the in the security group tags is our hint to AWS about using aws-karpenter for autoscaling nodes and pods in this cluster. You can get the VPC up and running via the

terraform plan
terraform apply

commands, it’s a good practice to define key values that you will need in other modules as outputs to this module run, also, we save the state in a S3 bucket as our TF builds run from a Jenkins Salve on Fargate with ephemeral storage. You’d see the following values in the console output of the terraform apply command if you’ve included publishing the VPC and security group IDs in the of your vpc module.

security_group_id = "sg-dkfjksdhf83983c883"
vpc_id = "vpc-2l4jc2lj4l2cbj42"

With this we have our VPC ready, let’s deploy the EKS cluster with Node Groups and Karpenter.

Deploying EKS Cluster with Node Group Workers and Karpenter

Add the following code to you terraform module to include EKS

It’s the same "" tag at play here too, and that’s it! You have an eks cluster with Karpenter managed provisioning ready!

Configuring Karpenter Provisioners

Now that we have a cluster ready let’s have a look at using Karpenter to manage the Pods. We’ll define provisioners for different purposes and then associate pods to each of them.

Provisioner for Nodes running Spot Instances

This is good alternative to Fargate, specially for running the one-off workloads which do not live beyond the job completion. Here’s an example of a Karpenter provisioner using spot instances.

To use this provisioner add the following tag to the nodeSelector in kube deployment.

nodeSelector: default

This will provision the pods to run on spot instances.

Provisioner for Nodes running On-Demand Instances

Here’s a sample of how to use on-demand node for worker nodes, and schedule pods on it. The following file defines a provisioner for on-demand instances

Once again we can utilise the nodeSelector in kube deployment yaml to provision pods on these nodes

nodeSelector: on-demand


This is a simplified example of how to get started with Karpenter on AWS EKS. production grade deployments require more nuanced provisioner definitions including but not limited to resource limits, eviction policies as well.

Attribution Image Credits: Photo by Growtika on Unsplash