Kubernetes has become the standard answer to almost any question about running containers. The 2025 CNCF Annual Cloud Native Survey found that 82% of container users now run it in production. For many teams, the choice gets made early and with little debate.
That choice carries a long-term commitment. The Kubernetes project ships roughly three minor releases a year and supports each one for about 14 months. Every cluster needs a planned upgrade at least once a year, along with ongoing care for the add-ons and security controls around it.
On AWS, teams have another managed option in Amazon ECS. It runs containers at scale with a smaller operational footprint, and it meets the requirements of a large share of workloads. Kubernetes still has a clear place for workloads that depend on its ecosystem or its portability. Choosing between the two is an infrastructure decision with years of operational consequences.
If your team approached its container platform from a blank page today, would Kubernetes still be the first answer on the board?
New to Amazon ECS? Check out our introductory series: Deploying Your First Container on Amazon ECS
Why Kubernetes Became the Default
Kubernetes earned its position. Google open-sourced it in 2014, and it became the first project hosted by the Cloud Native Computing Foundation. Several forces then pushed it to the top of every shortlist.
A Deep Ecosystem
Kubernetes provides a standard API that a vast range of tools build on. Package managers, GitOps controllers, service meshes, and policy engines all assume a Kubernetes cluster underneath. Teams that adopt it gain access to that tooling, and to the community knowledge around it.
Portability Across Environments
Each major cloud provider offers a managed Kubernetes service, including Amazon EKS and Google Kubernetes Engine. The same platform runs in on-premises data centers as well. Workloads defined as Kubernetes manifests can move between environments with fewer changes, which is appealing to organizations wary of vendor lock-in.
The Safe Choice for Hiring and Careers
Kubernetes experience is a common requirement in infrastructure roles, and engineers know it. Using the same platform most of the industry uses makes hiring easier to plan. It also gives engineers skills that carry from one job to the next; few people get questioned for picking the market leader.
What Amazon ECS Handles For You
Amazon ECS is AWS’s own container orchestration service. AWS describes it as an opinionated way to run containers at scale. In practice, AWS makes many of the platform decisions that Kubernetes leaves to the team operating the cluster.
No Orchestration Fee or Control Plane Upkeep
There is no additional charge for ECS orchestration: you pay for the compute your containers run on. AWS operates the control plane, and there is no Kubernetes-style version cycle for your team to track and plan upgrades around.
Clusters cost nothing on their own. Giving each environment its own cluster adds no orchestration fees.
Native AWS Integration
There are several important factors that are worth expounding on:
- Identity: IAM task roles give each task its own permissions using the IAM policies teams already manage.
- Load balancing: ECS services register with Application Load Balancer and Network Load Balancer target groups automatically.
- Secrets: Task definitions can pull values from Secrets Manager or Systems Manager Parameter Store at launch.
- Service-to-service traffic: ECS Service Connect handles service discovery and connections between services with no separate mesh to run.
- Safer deployments: The deployment circuit breaker detects failing deployments and can roll them back automatically.
Each of these covers a job that a Kubernetes cluster would typically handle with an add-on, installed by the team and kept compatible across upgrades.
Flexible Compute Choices
ECS supports several compute options, so teams can decide how much of the underlying infrastructure they manage:
- AWS Fargate runs each task with no servers to provision or patch. You size each task’s CPU and memory and pay for what it uses.
- ECS Managed Instances open up a wider range of EC2 instance types. AWS takes on the instance operations for a per-instance management fee.
- Self-managed EC2 capacity suits teams that need full control of the host, such as custom AMIs or specialized agents.
- ECS Anywhere extends the same control plane to on-premises servers for hybrid needs.
What You’re Still Responsible For
ECS reduces platform work, but a meaningful share of infrastructure responsibility stays with your team. Under the AWS shared responsibility model, AWS secures the underlying infrastructure. Customers remain responsible for how they configure and use the services built on top of it.
On ECS, that responsibility includes:
- Network design: VPC layout, subnets, security groups, and how traffic enters and leaves your services.
- Access control: Least-privilege IAM for tasks, pipelines, and the people who deploy them.
- Infrastructure as Code (IaC): Task definitions, services, load balancers, and supporting resources defined in code, versioned, and reviewed.
- Visibility and response: Logging, metrics, alerting, and a clear plan for when something breaks.
These are the same disciplines a Kubernetes platform depends on. With ECS, more of your team’s infrastructure time can go toward them, since the orchestrator itself needs far less care.
If you’re new to IaC, start from the top: How to Use Infrastructure as Code with Terraform on AWS
Matching the Workload to the Platform
Signs That ECS is the Better Fit
- Your organization runs on AWS and has no funded plan to run workloads on another cloud.
- Most workloads are stateless, such as web applications, APIs, queue workers, and scheduled jobs.
- You run a small to moderate number of services, and each team deploys its own.
- No dedicated platform team exists to own a cluster full time.
- You want serverless containers through Fargate with little tuning.
Signs That Kubernetes is Warranted
- Running across multiple clouds or on premises is a documented requirement with a budget behind it.
- Your workloads rely on Kubernetes-native tooling, such as operators or GitOps controllers.
- You run AI or ML workloads that need GPU scheduling or custom schedulers. The 2025 CNCF survey found that 66% of organizations hosting generative AI models use Kubernetes for some or all of their inference.
- You operate a large multi-tenant platform that serves many internal teams.
- Key third-party software ships as Helm charts or operators.
- An established platform team has the skills and the time to run clusters.
You Don’t Have to Pick Just One
Teams can use more than one container service on AWS. Amazon Elastic Kubernetes Service (EKS) is AWS’s managed Kubernetes service. AWS runs the Kubernetes control plane, and your team handles the add-ons and version upgrades. Many organizations run most services on ECS and move specific workloads to EKS where Kubernetes adds clear value.
Two details make a mixed approach practical:
- Moving a service from one platform to the other means rewriting its deployment definitions and pipelines. The application code and container images carry over unchanged.
- Shared foundations, such as VPC design and IAM, can serve both platforms when they’re defined in code.
Starting on ECS keeps the path to Kubernetes open for the day a workload needs it.
Questions to Consider Before Choosing
Bring these into your next planning conversation:
- Who owns cluster upgrades, and where does that work sit on the roadmap?
- Is portability a stated requirement with a budget, or a “just in case”?
- What does the workload need from the scheduler that ECS can’t provide?
- How many clusters will you run across environments? On Amazon EKS, each one carries an hourly fee of $0.10, rising to $0.60 once its Kubernetes version passes 14 months and moves into extended support.
- Who reviews security configuration each time the platform changes?
Start With the Workload, Then Revisit the Container Platform
Platform decisions age. A service that fits Amazon ECS well today may need Kubernetes-native tooling in two years, and the reverse happens too.
Record the reasoning behind your choice and set a trigger for reviewing it, such as a major product change or a shift in team structure. A written decision gives future teams a clear starting point when circumstances change.
Or work with a team that runs both.
SMS designs and supports container platforms on both Kubernetes and Amazon ECS. Our senior engineers have run each in production, and we use Kubernetes ourselves where it fits. As an AWS Partner, we work closely with AWS services and guidance, so our recommendations reflect how these platforms behave in real AWS environments.
If you’re weighing a platform choice or rethinking one you’ve already made, talk to our team about your workloads.
