Comparison

Updated October 25, 2026

· ~3 min read

EKS Nodes in 2026: Auto Mode vs Self-Managed Karpenter vs Managed Node Groups vs Fargate

EKS
EKS Auto Mode
Karpenter
Kubernetes
Fargate
Node groups

Choosing EKS is only half the decision; the other half is who runs the nodes. EKS Auto Mode, launched at the end of 2024 and steadily extended since, runs Karpenter, the AWS Load Balancer Controller and the EBS CSI driver off-cluster, launches Bottlerocket nodes for pending pods, consolidates them, and charges a per-instance fee for doing so. Karpenter run yourself does much of the same scheduling with no fee and full control. Managed node groups are the older, simpler model of Auto Scaling groups that EKS helps you update. And Fargate runs pods with no nodes at all, with limits.

AWS reports that Karpenter inside Auto Mode scales out 43% faster and consolidates up to 69% faster after optimisations shipped through 2025 and 2026.

At a glance

EKS Auto Mode

Karpenter (self-managed)

Managed node groups

Fargate

Who runs the node autoscaler

AWS, off-cluster

You, in-cluster

Cluster Autoscaler or Karpenter, yours to run

Not applicable

Node OS

Bottlerocket, managed

Your choice of AMI

EKS-optimized AL2023, Bottlerocket or custom

Not exposed

Load balancer and EBS controllers

Managed by AWS

You install and upgrade

You install and upgrade

Load balancer controller with IP targets; no EBS volumes

Fee on top of EC2

Per instance-hour, e.g. $0.02064 for m5a.xlarge

None

None

Fargate pricing per pod

GPUs, EFA, placement groups

Yes — EFA and placement groups since July 2026

Yes

Yes

No

Node upgrades

Automatic

Drift-based replacement you configure

You trigger an update per group

Restart pods

Control

Lowest

Highest

Medium

Lowest

Operational work

Lowest

Medium to high

Medium

Low

Is the Auto Mode fee worth it?

For an m5a.xlarge the Auto Mode fee is about $0.021 an hour against an On-Demand price of about $0.17 — roughly 12%, and a smaller share of the effective price once Savings Plans apply to the EC2 part. What it buys is the work that most often goes wrong: keeping Karpenter, the load balancer controller and the storage driver compatible with each Kubernetes version, patching node operating systems, and replacing nodes on schedule. For a team without a dedicated platform engineer that is cheap. For a team with several, who already run Karpenter well, it may not be.

Moving an existing cluster to Auto Mode

Auto Mode can be enabled on an existing cluster and run alongside managed node groups, so you can move workloads gradually: enable it, create a NodePool, cordon and drain an existing node group while pods reschedule onto Auto Mode nodes, then remove the group. Check anything that assumed a specific AMI or host agent — Auto Mode nodes run Bottlerocket — and remove the self-managed copies of the controllers Auto Mode now runs, so two of them are not fighting over the same load balancers.

Which should this cluster use?

Question 1 of 2

Do you need custom AMIs, host-level agents or node configuration Auto Mode does not allow?

Our verdict

Use EKS Auto Mode for new clusters unless you have a specific reason not to — it removes node patching, the controllers that most often break during upgrades, and most capacity planning, for a fee of roughly a tenth of a typical instance's On-Demand price. Run Karpenter yourself when you need control Auto Mode does not give you (custom AMIs, unusual node configuration, your own add-on versions) and have the people to own it. Keep managed node groups for small, static clusters or workloads that need predictable nodes. Use Fargate on EKS only for isolated, low-volume pods — it does not support DaemonSets or GPUs.

Related solutions

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Get an EKS platform that stays current

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As of October 25, 2026. Provided as is, for general information, and accurate to the best of our knowledge on the date shown. Not legal, compliance, tax, financial or other professional advice. Prices, limits and vendor services change; check current vendor documentation before relying on anything here. Terms of use.