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- Top 3 Ways to Run Docker Container on AWS
Top 3 Ways to Run Docker Container on AWS
Running Docker containers on AWS gives you flexibility and scale—but with multiple services to choose from, it’s not always clear which one is right for your workloads. Should you go with ECS on Fargate, EKS, or Elastic Beanstalk? Each option has its tradeoffs in terms of complexity, flexibility, and operational overhead.
In this post, we’ll explain what Docker containers are, explore the three most common ways to run them on AWS, compare each option across key dimensions, and help you decide which one fits your needs.
What are Docker Containers?
Docker containers are self-contained environments that bundle your application code with all its dependencies, so it runs the same way everywhere—whether on a developer’s laptop or in a production cluster. Unlike virtual machines, containers are lightweight and start almost instantly, making them ideal for deploying microservices, automating tests, or spinning up reproducible environments on demand. They’ve become the standard for modern app delivery because they simplify packaging, speed up deployment, and reduce configuration drift.
3 Ways to Run Docker Containers on AWS
AWS offers multiple services for running containers, each designed for different levels of control, complexity, and automation. Below are the three most common ways to run Docker workloads on AWS.
1. Using AWS ECS (Elastic Container Service) with AWS Fargate
ECS with Fargate is AWS’s most hands-off option for running containers. You define your container requirements, and Fargate handles provisioning, scaling, and managing the compute infrastructure. There’s no need to manage EC2 instances or clusters—just specify CPU, memory, and networking, and go.
It’s ideal for teams that want to deploy containers quickly without worrying about servers or capacity planning.
You can deploy using the ECS console, the AWS CLI, or IaC tools like Terraform and AWS CDK. It supports service discovery, autoscaling, and integration with other AWS services like CloudWatch and IAM.
2. Using AWS Elastic Beanstalk (EB) with Single Container Docker
Elastic Beanstalk abstracts away infrastructure even further. You upload your Docker image, and EB provisions the environment, handles load balancing, and automates deployments. While it’s great for simple applications and rapid prototyping, it’s less flexible and harder to tune for production-scale container workloads.
There are three ways to deploy Docker containers on Elastic Beanstalk:
- Use a
Dockerrun.aws.jsonfile that references your container image - Create a
Dockerfileand upload it directly to Elastic Beanstalk - Zip your
Dockerfilewith any supporting files and upload the archive
You can launch, monitor, scale, and stop your application from the Elastic Beanstalk console—treating your containerized app as a single unit.
3. Amazon Elastic Kubernetes Service (EKS)
EKS is AWS’s managed Kubernetes service. It offers the full power and flexibility of Kubernetes but requires more upfront setup and ongoing management. You get fine-grained control over scheduling, networking, and scaling—but that also means managing node groups, IAM roles, and Kubernetes configs.
You deploy using standard Kubernetes tools (kubectl, Helm, etc.) and define your containers in Kubernetes manifests (e.g., Deployments, StatefulSets). This gives you full control over scheduling, networking, and scaling—but also comes with more complexity and operational responsibility.
EKS is best suited for teams with existing Kubernetes experience or those who need advanced orchestration features like custom scheduling, network policies, and complex service meshes.
Comparison Between Ways to Run Docker Container on AWS
Let’s summarize with a quick table:
| Feature | ECS + Fargate | EKS (Kubernetes) | Elastic Beanstalk |
|---|---|---|---|
| Complexity | 🔵 Low – Simple setup, abstracted infra | 🔴 High – Steep learning curve | 🟢 Very Low – Minimal setup |
| Flexibility | 🟡 Moderate – Limited to ECS features | 🔵 High – Full Kubernetes control | 🔴 Low – Opinionated and limited |
| Operational Effort | 🔵 Low – No server management | 🔴 High – Manage nodes, upgrades | 🟢 Very Low – AWS manages everything |
| Maturity of AWS Integrations | 🟢 High – Built by AWS for AWS | 🟡 Medium – Many integrations available | 🟢 High – Integrates well with AWS |
| Inter-service Communication (Microservices) | 🟢 Supported with ECS Service Mesh | 🔵 Full Kubernetes service networking | 🔴 Limited, not microservice-friendly |
| Cloud Agnostic? | 🔴 No – AWS-only | 🟢 Yes – Kubernetes is portable | 🔴 No – AWS-only |
| Multiple Applications per Host? | 🟢 Yes – Tasks share compute | 🟢 Yes – Pods on shared nodes | 🔴 No – One app per environment |
ECS Cost Optimization: The Complete Guide
- Complexity: ECS with Fargate is relatively simple to get started with—there’s no need to manage servers or clusters, and you can deploy containers using a straightforward task definition. EKS, on the other hand, has a steeper learning curve, requiring familiarity with Kubernetes concepts like pods, services, and ingress controllers. Elastic Beanstalk is the most beginner-friendly option, allowing you to deploy a containerized app with minimal configuration, but that simplicity comes at the cost of flexibility.
- Flexibility: EKS offers the highest degree of flexibility, giving you full control over scheduling, scaling, networking, and third-party integrations through the broader Kubernetes ecosystem. ECS provides moderate flexibility, allowing you to define resource requirements, networking, and deployment strategies, but you’re still operating within the ECS model. Elastic Beanstalk is limited in what you can customize—it’s designed to be hands-off and prescriptive, which makes it easy to use but not suitable for complex architectures.
- Operational Effort: ECS with Fargate is designed to minimize operational overhead—you don’t need to provision infrastructure or handle scaling manually. With EKS, you’re responsible for managing the control plane configuration, node groups (unless you use Fargate), version upgrades, and cluster security. Elastic Beanstalk handles provisioning, deployment, and environment management automatically, but it can be opaque when something goes wrong, making debugging more difficult in production.
- Maturity of AWS Integrations
ECS and Elastic Beanstalk are deeply integrated with AWS services like CloudWatch, IAM, ALB, and CloudFormation. Everything is built to work natively within the AWS ecosystem, with minimal setup. EKS also supports strong AWS integrations, but it often requires additional components—like the AWS Load Balancer Controller or IAM Roles for Service Accounts (IRSA)—to fully leverage those integrations, especially when compared to ECS. - Inter-service Communication for Microservices: Both ECS and EKS support microservices architectures well. ECS supports service discovery via AWS Cloud Map and can integrate with App Mesh for more advanced routing. EKS, leveraging Kubernetes’ native service discovery and networking, is ideal for teams adopting service mesh patterns and complex dependency management. Elastic Beanstalk, however, is more suitable for standalone applications—it doesn’t provide built-in service discovery or tools for managing internal service-to-service communication at scale.
- Cloud Agnostic: EKS stands out as the only cloud-agnostic option here, as it runs standard Kubernetes workloads that can be ported to other cloud providers or on-prem clusters with minimal changes. ECS and Elastic Beanstalk are AWS-specific services with deployment models that don’t translate outside the AWS ecosystem, making them less flexible for organizations pursuing multi-cloud or hybrid strategies.
- Multiple Applications per Host:
ECS and EKS both support running multiple applications on the same underlying infrastructure—tasks in ECS and pods in EKS can be efficiently scheduled across shared compute resources. Elastic Beanstalk is more limited in this regard, as each environment is designed to host a single containerized application. Running multiple apps requires separate environments or custom workarounds, which adds complexity and overhead.
Which is the Best Way to Run your Docker Workloads on AWS?
While each service has its place, ECS with Fargate is often the best default choice for most teams running Docker workloads on AWS. It strikes a strong balance between simplicity, flexibility, and scalability—without the need to manage infrastructure or dive into the complexity of Kubernetes. You get deep AWS integrations, native support for microservices, and enough control to customize deployments without taking on the operational burden of managing clusters.
EKS is a better fit for organizations already invested in Kubernetes or those with advanced orchestration needs. It offers maximum flexibility but requires more expertise and operational maturity. Elastic Beanstalk, while easy to use, is best suited for single-container applications and rapid prototyping—not for large-scale or production-grade microservices.
If your goal is to run containers reliably, securely, and with minimal overhead—especially in a fully serverless model—ECS with Fargate is the fastest path to production.
Optimize container costs with nOps
If you’re looking to optimize your container utilization and costs, nOps can help. Just simply integrate it with your Karpenter, Cluster Autoscaler or Auto Scaling Groups to start saving. nOps offers proprietary AI-driven management of instances for the best price in real time. It continually analyzes market pricing and your existing commitments to ensure you are always on the best blend of Spot, Reserved, and On-Demand, gracefully replacing nodes before termination. Here are a few of the benefits:
- Hands free. Copilot automatically selects the optimal instance types for your EKS workloads, freeing up your time to focus on building and innovating. As your dynamic usage scales, Copilot continually reconsiders your instance placement.
- Effortless Spot savings. Copilot makes it easy to benefit from Spot savings. nOps predicts terminations 60 minutes in advance, putting you on diverse and safe Spot options to greatly reduce unexpected interruptions. In fact, our Spot SLAs are the same as AWS On-Demand.
- No vendor-lock in or upfront cost. Just plug in your AWS-native EKS clusters to start saving effortlessly, and change your mind at any time.
Frequently Asked Questions
Can you run a Docker container on AWS?
Yes, you can run Docker containers on AWS using services like ECS (Elastic Container Service), EKS (Elastic Kubernetes Service), Fargate, or even EC2. ECS and Fargate are the most straightforward options for running Docker without managing infrastructure. You simply define your container image, resource requirements, and networking configuration, and AWS handles the rest.
How do I run Docker containers in the cloud?
To run Docker containers in the cloud, choose a container orchestration or compute platform—such as AWS ECS, EKS, or Fargate. Push your Docker image to a container registry (e.g., Amazon ECR or Docker Hub), define how the container should run (CPU, memory, port mappings), and deploy it via the cloud provider’s console or CLI. Services like AWS Fargate let you run containers without managing servers.
How to run a container in ECS?
To run a container in ECS, first push your Docker image to Amazon ECR or another registry. Then, create a task definition in ECS that describes the image, resources, and networking settings. Choose a launch type—either EC2 (self-managed instances) or Fargate (fully managed). Finally, create a service or run the task manually.
What is the difference between Docker and ECS?
Docker is a tool for building and running containers—it defines how your application and its dependencies are packaged. ECS (Elastic Container Service) is a container orchestration platform provided by AWS that runs and manages those containers at scale. You use Docker to create the container image, and ECS to deploy, schedule, and scale it across your infrastructure. In short, Docker defines what to run; ECS decides where and how to run it in the cloud.
