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EKS Auto Mode is a good fit if you want AWS to manage more of your Kubernetes data-plane infrastructure and can accept managed, immutable nodes without direct SSH or SSM access. It is a weaker fit if your team needs custom node operating systems, direct node access, or full control over scaling and infrastructure components. AWS’s Terraform walkthrough offers a runnable starting point, but it is a workload-oriented sample—not a production-ready configuration for every cluster.
What EKS Auto Mode manages—and what stays yours
EKS Auto Mode extends AWS management beyond the Kubernetes control plane. Its core capabilities include compute autoscaling, pod and service networking, application load balancing, cluster DNS, block storage, and GPU support. It integrates Karpenter-based scaling and can consolidate unused capacity. AWS’s EKS Auto Mode documentation describes these managed capabilities.
AWS takes on infrastructure operations, not responsibility for your applications. You remain responsible for application container availability, security, and monitoring, as well as your VPC infrastructure and EKS cluster configuration. As AWS puts it: “Under EKS Auto Mode, customers continue to maintain responsibility for the application containers, including availability, security, and monitoring.”
Know the node constraints
Auto Mode nodes use locked-down, immutable Bottlerocket variants. Direct SSH and SSM access are not available. Nodes have a maximum lifetime of 21 days and are replaced; disruption controls can sometimes block upgrades, requiring operator intervention. These constraints suit teams willing to work through Kubernetes and AWS-managed interfaces, but can conflict with workloads or operating practices that depend on node-level access or extensive OS customization.
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Decide whether Auto Mode fits your team
| Decision area | Auto Mode may fit if… | Consider self-managed components if… |
|---|---|---|
| Operations | You want AWS to manage nodes, scaling, and several cluster capabilities. | You are prepared to operate more infrastructure components yourself. |
| Node access | You can work without SSH/SSM and with managed, immutable node images. | You need direct node access or custom node-level configuration. |
| Scaling and disruption | Built-in scaling, consolidation, lifecycle, and disruption controls fit your workloads. | You need to own and tune those mechanisms. |
| IAM and networking | Your roles, trust policies, VPC, and subnets can meet EKS requirements. | Your architecture would need substantial changes and you want to evaluate alternatives before adopting the managed model. |
| Cost | Your regional costs work for the workload and capacity you plan to run. | You want to compare operating models using the same workload assumptions before choosing. |
There is no established universal cost winner: compare the costs for your region, capacity, instances, storage, load balancers, and observability needs. The other meaningful trade-off is operational ownership. AWS’s tutorial has separate Auto Mode and self-managed Karpenter paths; the latter involves installing and configuring more components, including Karpenter and networking add-ons.
Auto Mode also supports custom NodePools and NodeClasses alongside defaults, for example to set instance selection, workload isolation, or ephemeral storage controls. AWS advises against editing its default NodePools and NodeClasses. See AWS’s Auto Mode documentation for details.
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Check prerequisites before running Terraform
AWS’s advanced cluster creation guidance calls for an existing, qualifying VPC and subnets, appropriate IAM permissions, Auto Mode cluster permissions and trust, and a node IAM role when built-in node pools are enabled. EKS access entries are required, the Kubernetes version must be 1.29 or greater, and cluster networking needs at least two subnets. Review AWS’s Auto Mode cluster creation guide and cluster creation documentation against your account and network design.
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- Confirm the AWS account and target region before applying resources.
- Check that the VPC and at least two suitable subnets are ready.
- Prepare the cluster IAM role, permissions, trust, and—if using built-in node pools—the node IAM role.
- Decide whether the built-in node pools suit your workloads before deployment.
- Estimate costs for the region and resources you intend to use.
Set up the AWS Terraform sample
AWS’s official AI/ML walkthrough is a useful example to run, not a general-purpose production module prescription. It directs readers to the aws-samples/sample-eks-docs repository and the ai-ml/set-up-cluster/terraform/auto-mode directory. The tutorial defaults to us-east-2; it describes using a region variable to select another region.
- Install and check the prerequisites. Use the Terraform, kubectl, AWS CLI, and jq versions listed in the prerequisite section, checking the live AWS walkthrough for changes.
- Prepare your AWS foundation. Confirm the account, region, VPC, subnets, and required IAM roles, permissions, and trust are in place.
- Clone the sample repository. Follow the repository and directory instructions in AWS’s walkthrough, then change into
ai-ml/set-up-cluster/terraform/auto-mode. - Initialize Terraform. Run
terraform initfrom that directory. - Review the deployment inputs. Confirm the region and intended resources before continuing; do not assume the sample’s defaults are appropriate for your account or production environment.
- Apply the configuration. Run
terraform applyand review the proposed changes before approving them. AWS says deployment takes a few minutes in this tutorial. - Harden the sample Grafana exposure. In the tutorial configuration, Grafana’s load balancer defaults to public HTTP with default credentials. At minimum, restrict the source CIDR and change the admin password; consider internal-only access and TLS.
- Clean up when finished. Destroy tutorial resources you no longer need, following the walkthrough’s cleanup instructions.
The sample can create chargeable EKS, GPU, Application Load Balancer, and managed Prometheus resources. Costs depend on region and usage; estimate them for your own workload before applying, and remove the resources when the tutorial is complete.
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Choose Auto Mode or the self-managed Karpenter path deliberately
The sample repository has distinct terraform/auto-mode/ and terraform/karpenter/ paths. The choice affects who operates key cluster components: Auto Mode delegates more of the infrastructure behavior to AWS, while the self-managed path requires you to install and configure more components. AWS says switching between those paths requires destroying the cluster and starting over, so choose before deployment rather than treating the paths as interchangeable settings.
This walkthrough does not establish a production-ready Terraform module or a verified, provider-versioned HCL configuration. For production, select and pin the Terraform provider or module versions you intend to use, validate their current fields against their official documentation, and test the configuration in an appropriate environment before relying on it. Do not treat a tutorial apply as proof that IAM, networking, workload security, availability, monitoring, or cost controls are production-ready.
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