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In this guide, we’ll walk through real-time auto scaling on Amazon EKS using three compute options:
  1. Managed Node Groups
  2. Fargate Profiles
  3. Karpenter Provisioner
By the end, you’ll understand how to deploy workloads that scale automatically based on demand.

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1. Cluster Setup: Managed Node Group & Fargate Profiles

We’ve created:
  • A managed Node Group named main (desired capacity: 2)
  • Two Fargate profiles: default and fargate (selects namespace: fargate)
The image shows an AWS Elastic Kubernetes Service (EKS) console with details about node groups and Fargate profiles. It indicates no nodes are present, but there is one active node group and two active Fargate profiles.
When you schedule a Pod in the fargate namespace, the Fargate mutating webhook injects a custom scheduler that routes Pods to serverless Fargate compute.
The image shows an AWS console page for configuring a Fargate profile in an Elastic Kubernetes Service (EKS) cluster, with the status marked as active and a section for pod selectors.

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2. Verifying Webhooks & Node Status

First, confirm the Fargate mutation webhook is installed: 
kubectl get mutatingwebhookconfigurations.admissionregistration.k8s.io

NAME                                           WEBHOOKS   AGE
0500-amazon-eks-fargate-mutation.amazonaws.com 2          4h39m
pod-identity-webhook                           1          4h45m
vpc-resource-mutating-webhook                  1          4h45m
Next, list the current nodes in your cluster (you should see only the managed nodes): 
kubectl get nodes

NAME                                              STATUS   ROLES    AGE   VERSION
i-05b0938045882bc66.us-west-2.compute.internal    Ready    <none>   4h    v1.29.0-eks-5e0fdde
i-0b67dcfad12062f1d.us-west-2.compute.internal    Ready    <none>   4h    v1.29.0-eks-5e0fdde
View the main Node Group details via eksdemo or your preferred CLI: 
eksdemo get mng -c kodekloud

+-------+--------+------+-------+-----+-----+-----------------------------+-----------+
| Age   | Status | Name | Nodes | Min | Max | Version                     | Type      |
+-------+--------+------+-------+-----+-----+-----------------------------+-----------+
| 4h    | ACTIVE | main | 2     | 0   | 10  | ami-09167e9f270af0d8 (eks)  | ON_DEMAND |
+-------+--------+------+-------+-----+-----+-----------------------------+-----------+
We currently have no Cluster Autoscaler installed, so we’ll adjust the Node Group sizes manually below.

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3. Manual Scaling of the Managed Node Group

To force-scale the main Node Group down to 1 node: 
eksdemo update mng main -c kodekloud --min 1 --max 1

Updating nodegroup with 1 Nodes, 1 Max...done
Within a minute, one managed node will terminate.

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4. Deploying Workloads to Fargate

Let’s create a namespace and a Deployment that matches the fargate profile: 
apiVersion: v1
kind: Namespace
metadata:
  name: fargate
---
apiVersion: apps/v1
kind: Deployment
metadata:
  name: fargate-nginx
  namespace: fargate
spec:
  replicas: 1
  selector:
    matchLabels:
      app: fargate-nginx
  template:
    metadata:
      labels:
        app: fargate-nginx
    spec:
      terminationGracePeriodSeconds: 0
      containers:
        - name: fargate-nginx
          image: public.ecr.aws/nginx/nginx:latest
Apply the manifest: 
kubectl apply -f fargate-deploy.yaml
Watch the Pod in Pending state until Fargate provisions a node: 
kubectl get pods -n fargate --watch
Describe the pending Pod to verify the custom scheduler: 
kubectl get pod fargate-nginx-<id> -n fargate -o yaml

spec:
  schedulerName: fargate-scheduler
  tolerations:
    - key: node.kubernetes.io/not-ready
      operator: Exists
      effect: NoExecute
      tolerationSeconds: 300
    - key: node.kubernetes.io/unreachable
      operator: Exists
      effect: NoExecute
      tolerationSeconds: 300
Once Fargate provisioning completes, you’ll see a new node: 
kubectl get nodes

NAME                                                               STATUS
fargate-ip-192-168-138-113.us-west-2.compute.internal              Ready
i-05b0938045882bc66.us-west-2.compute.internal                     Ready
Scale the Fargate deployment to 5 replicas: 
kubectl scale deploy fargate-nginx -n fargate --replicas 5
kubectl get pods -n fargate

NAME                                   READY   STATUS    AGE
fargate-nginx-58f48f6b79-7ggz5         0/1     Pending   4s
fargate-nginx-58f48f6b79-gldtV         0/1     Pending   4s
fargate-nginx-58f48f6b79-h8pzw         0/1     Pending   4s
fargate-nginx-58f48f6b79-p46sq         1/1     Running   2m24s
fargate-nginx-58f48f6b79-sjzxz         0/1     Pending   4s
Fargate creates one node per Pod, which can add provisioning latency for rapid scaling.

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5. Standard Nginx Deployment on Managed Nodes

Deploy a typical Nginx workload in the default namespace: 
apiVersion: apps/v1
kind: Deployment
metadata:
  name: nginx
spec:
  replicas: 2
  selector:
    matchLabels:
      app: nginx
  template:
    metadata:
      labels:
        app: nginx
    spec:
      terminationGracePeriodSeconds: 0
      containers:
        - name: nginx
          image: public.ecr.aws/nginx/nginx:latest

kubectl apply -f nginx-deploy.yaml
kubectl get pods

NAME                     READY   STATUS    AGE
nginx-56cd7bd595-abcde   1/1     Running   30s
nginx-56cd7bd595-fghij   1/1     Running   30s
These Pods schedule immediately on existing on-demand nodes.

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6. Dynamic Scaling with Karpenter

Karpenter automatically provisions compute when Pods remain unscheduled due to resource constraints.
Make sure you’ve installed Karpenter and configured the required IAM roles. See the Karpenter documentation for setup instructions.
  1. Verify Karpenter pods: 
    kubectl get pods -n kube-system | grep karpenter
  2. Scale the Nginx deployment to 25 replicas: 
    kubectl scale deploy nginx --replicas 25
  3. Add CPU requests to force new node provisioning: 
    kubectl set resources deployment nginx --requests=cpu=500m
  4. Watch Pods and Nodes: 
    kubectl get pods --all-namespaces --watch
kubectl get nodes
    Example of new C5 nodes: 
    NAME                                                      STATUS   AGE    VERSION
i-048b7c8a501cda49d.us-west-2.compute.internal            Ready    66s    v1.29.0-eks-5e0fdde
i-0c1d8c0722d4758b1.us-west-2.compute.internal            Ready    25s    v1.29.0-eks-5e0fdde
# ... existing fargate and managed nodes ...
  5. Inspect a Karpenter-provisioned node: 
    kubectl get node i-048b7c8a501cda49d -o yaml

    metadata:
  labels:
    beta.kubernetes.io/instance-type: c5.2xlarge
    karpenter.amazonaws.com/instance-family: c5
    karpenter.k8s.aws/instance-cpu: "8"
    karpenter.sh/managed-by: karpenter
spec: {}

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7. Karpenter Default Provisioner Configuration

View and describe the default Provisioner to see its constraints: 
kubectl get provisioners

NAME
default

kubectl get provisioner default -o yaml

spec:
  requirements:
    - key: kubernetes.io/arch
      operator: In
      values: ["amd64"]
    - key: kubernetes.io/os
      operator: In
      values: ["linux"]
    - key: karpenter.sh/capacity-type
      operator: In
      values: ["on-demand","spot"]
    - key: karpenter.k8s.aws/instance-category
      operator: In
      values: ["c","m","r"]
    - key: karpenter.k8s.aws/instance-generation
      operator: Gt
      values: ["2"]
  limits:
    cpu: 1000
status:
  resources:
    cpu: "16"
    memory: 31792072Ki
    pods: "116"
This provisioner restricts instances to Linux/AMD64 of category C, M, or R (generation > 2) and allows up to 1,000 CPUs.

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8. Summary: EKS Compute Options Comparison

Compute OptionDescriptionCharacteristics
Managed Node GroupAlways-on EC2 capacity with lifecycle APIsStable, version-managed nodes, manual or autoscaled
Fargate ProfilesServerless pods on demandOne node per Pod, isolation, longer startup latency
KarpenterDynamic, request-driven node provisioningFast scale-out, flexible instance types, cost-efficient

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