ECS vs EKS: which should a startup choose?

For most startups with a small team and fewer than a dozen services, ECS is the better default: no control-plane fee, no cluster upgrades, and fewer moving parts to learn. EKS becomes the right choice when you need the Kubernetes ecosystem, portability across clouds or on-premises, or you already have people who run Kubernetes well.

Neither choice is permanent. Your application ships as container images either way, so the migration cost later is mostly in deployment manifests and platform tooling, not in your code.

The short comparison

ECS is an AWS-native orchestrator with almost no platform to operate. EKS is managed Kubernetes: AWS runs the control plane, you run everything around it.

Cost: the control-plane fee is the smallest part

EKS charges $0.10 per cluster per hour, which works out to about $73 a month per cluster for a 730-hour month. ECS charges nothing for orchestration. Compute costs the same on both, because both run on the same EC2 instances or Fargate capacity.

The fee matters more than it looks once you multiply it. A typical setup of production, staging and a dev cluster is three fees. And if a cluster falls behind on upgrades, extended support raises it to $0.60 per cluster per hour, six times the standard rate. Extended support is enabled by default, so an unattended cluster drifts onto the higher price without anyone deciding to pay it.

The bigger cost is people. On EKS someone has to own the AWS Load Balancer Controller, the VPC CNI, CoreDNS, a node autoscaler, cluster upgrades every few months, and the security model of RBAC plus IAM. In our experience that is a meaningful part of one engineer's time even on a small cluster. On ECS most of that work does not exist.

There are newer managed options on both sides that shift this balance. EKS Auto Mode manages nodes and core add-ons for an extra per-instance fee on top of EC2, and ECS Managed Instances does something similar for ECS on EC2, also with a per-instance management fee. Both trade money for less node maintenance.

Operational effort, day to day

ECS asks you to understand task definitions, services, capacity providers and an ALB. EKS asks you to understand Kubernetes, and then the AWS-specific glue on top.

Here is the same small web service in both. The ECS version is a task definition fragment; the Kubernetes version is a Deployment that still needs a Service, an Ingress and the AWS Load Balancer Controller to receive traffic.

{
  "family": "api",
  "requiresCompatibilities": ["FARGATE"],
  "networkMode": "awsvpc",
  "cpu": "512",
  "memory": "1024",
  "runtimePlatform": { "cpuArchitecture": "ARM64", "operatingSystemFamily": "LINUX" },
  "taskRoleArn": "arn:aws:iam::123456789012:role/api-task",
  "executionRoleArn": "arn:aws:iam::123456789012:role/ecsTaskExecutionRole",
  "containerDefinitions": [
    {
      "name": "api",
      "image": "123456789012.dkr.ecr.eu-central-1.amazonaws.com/api:1.4.2",
      "portMappings": [{ "containerPort": 8080 }],
      "essential": true
    }
  ]
}

apiVersion: apps/v1
kind: Deployment
metadata:
  name: api
spec:
  replicas: 2
  selector:
    matchLabels:
      app: api
  template:
    metadata:
      labels:
        app: api
    spec:
      serviceAccountName: api
      containers:
        - name: api
          image: 123456789012.dkr.ecr.eu-central-1.amazonaws.com/api:1.4.2
          ports:
            - containerPort: 8080
          resources:
            requests:
              cpu: 500m
              memory: 1Gi

Neither is hard on its own. The difference shows up over a year: on EKS you will upgrade the cluster several times, update add-ons, and debug at least one problem that lives in the gap between Kubernetes and AWS networking or IAM. Pin image tags in both, by the way; shipping :latest is a problem on any orchestrator.

Ecosystem and portability

This is where EKS wins clearly. If you want Helm charts for third-party software, GitOps with Argo CD or Flux, Karpenter for node scaling, operators for databases or queues, or one deployment model across AWS, another cloud and on-premises, Kubernetes gives you that and ECS does not.

Be honest about whether you need it now. Portability is valuable when a customer contract requires on-premises or multi-cloud deployment, or when you sell software that customers install in their own clusters. "We might leave AWS one day" is rarely a good enough reason to take on Kubernetes at five engineers; our comparison of AWS, GCP and Azure for Greek startups covers why most teams stay on one cloud.

Fargate on both: not quite the same product

Fargate runs on both ECS and EKS, but the ECS version does more. On EKS, the documentation lists clear limits: no Fargate Spot, no DaemonSets, no privileged containers, no GPUs, no EBS volumes, and no Arm. The Fargate pricing page also notes that Arm and Windows are currently available only for ECS.

That matters for cost. On ECS you can run Graviton-based Fargate tasks and mix in Fargate Spot for workers and non-production. On EKS, most teams that care about cost end up on EC2 nodes managed by Karpenter or Auto Mode instead of Fargate.

Team skills and hiring

The best orchestrator is the one your team can operate at 3 a.m. If nobody on the team has run Kubernetes in production, EKS adds a learning curve at exactly the time you need to ship product.

In Greece the pool of engineers with real production Kubernetes experience is small and well paid, a point we cover in hiring a senior DevOps engineer in Greece. ECS is easier to hand over, easier to hire for, and harder to get badly wrong.

What stays the same either way

A lot of the work that makes a container platform good is identical on ECS and EKS, so don't let the orchestrator decision delay it.

• One IAM role per workload, never shared node credentials: task roles on ECS, Pod Identity or IRSA on EKS.
• Images in ECR, scanned, tagged immutably and built once in CI.
• Separate AWS accounts per environment, with the cluster or ECS services defined in Terraform.
• Logs, metrics and alerts wired up before the first production deploy, with retention set.
• Private subnets and a plan for egress, because container image pulls through a NAT gateway add up quickly.

Get these right and switching orchestrators later is a contained project. Get them wrong and neither ECS nor EKS will save you.

Decision guide

Use team size and service count as the first filter, then check the exceptions.

The exceptions that justify EKS early: a product that depends on Kubernetes operators or Helm-packaged software, contractual portability, ML or GPU-heavy workloads where the Kubernetes tooling is far ahead, or a team whose experience is mostly Kubernetes.

Moving from ECS to EKS later

Starting on ECS does not lock you in. Your images, registry, VPC, databases and CI stay the same; you rewrite deployment definitions and replace a few AWS integrations with their Kubernetes equivalents.

1. Keep the foundations portable from day one. Twelve-factor config through environment variables, health endpoints, stateless services, images built once and promoted by tag. Put infrastructure in Terraform so the EKS cluster is one more module.
2. Build the cluster next to ECS, not instead of it. Same VPC, same databases. Install the AWS Load Balancer Controller, a node autoscaler and your secrets approach (External Secrets or the Secrets Store CSI driver).
3. Translate one service. Task definition to Deployment plus Service, task IAM role to EKS Pod Identity, ECS service autoscaling to a HorizontalPodAutoscaler.
4. Shift traffic gradually. Weighted ALB target groups or weighted Route 53 records let you send 5%, then 50%, then 100% to the EKS version, with instant rollback to ECS.
5. Move the rest in batches, then delete the ECS services and update runbooks and on-call docs.

Your CI pipeline changes too: deploy steps go from updating an ECS service to applying manifests or committing to a GitOps repo. Use the move as a chance to fix the CI/CD anti-patterns you have collected along the way, and keep AWS access keyless with GitHub Actions OIDC.

Our default

For an early-stage startup on AWS, we start on ECS with Fargate, Graviton and Fargate Spot for non-production, all in Terraform. We move to EKS when the team, the service count or a customer requirement makes Kubernetes pay for its overhead, and we plan that move so it is a weekend of traffic shifting rather than a quarter-long project.

If you are weighing this decision, or already have an EKS cluster that takes more of your time than it should, our Kubernetes consulting covers both directions, and a planned move between platforms is part of our cloud migration work.

Frequently asked questions

Is ECS cheaper than EKS?

ECS has no orchestration fee, while EKS charges $0.10 per cluster per hour in standard support and $0.60 in extended support. Compute costs the same on both. The larger difference is engineering time: EKS needs regular cluster upgrades and add-on maintenance that ECS does not, which for a small team usually outweighs the fee itself.

Should a startup use Kubernetes or ECS?

Most startups with fewer than about ten engineers and ten services on AWS are better served by ECS on Fargate. Choose Kubernetes early if customers need on-premises or multi-cloud installs, your product depends on Kubernetes operators or Helm-packaged software, or your team already runs Kubernetes confidently.

Can I migrate from ECS to EKS later?

Yes. Container images, registry, VPC, databases and CI stay the same. You translate task definitions into Kubernetes Deployments and Services, move task IAM roles to EKS Pod Identity, and shift traffic gradually with weighted ALB target groups or Route 53 records, keeping ECS as an instant rollback.

Does Fargate work the same on ECS and EKS?

No. Fargate on EKS does not support Fargate Spot, DaemonSets, privileged containers, GPUs, EBS volumes or Arm, according to the AWS documentation. On ECS you can use Fargate Spot and Graviton-based Arm tasks, which makes Fargate a stronger and cheaper option there.