Containers improve application development with portability, efficiency, and scalability while accelerating deployments.
Amazon ECS and Kubernetes are two of the top choices for container orchestration, but how do they stack up against each other?
In this guide, we’ll break down the key differences, helping you choose the right solution for your containerization needs.
What Is Amazon ECS?
Amazon Elastic Container Service (ECS) is a fully managed service for running Docker containers at scale.
ECS organizes containers using task definitions, which specify how containers should run, including their configuration and resources. These definitions can launch individual tasks or manage multiple tasks as a service. An ECS service ensures a set number of tasks run simultaneously in a cluster, automatically maintaining availability and scaling applications.
ECS offers two launch types: EC2 and Fargate.
With the EC2 launch type, users have control over the EC2 instances hosting the containers. This allows for customization of compute resources and configurations. However, this requires hands-on management for provisioning, scaling, and maintenance.
With the Fargate launch type, users specify container resources, and AWS manages the infrastructure.
Fargate is preferred for simplicity and operational efficiency. But, the choice between Fargate and EC2 depends on specific use cases. Some users may prefer EC2 for greater control or cost considerations.
Read our complete guide on Amazon ECS Vs. EKS Vs. Fargate.
Amazon ECS benefits
Here are several compelling reasons to use ECS.
- Fully managed service. ECS orchestrates containers as AWS manages container infrastructure.
- Flexible launch options. Users can choose between AWS Fargate for serverless container deployment or Amazon EC2 for more control over the underlying instances.
- Scalability. ECS automatically adjusts the number of running containers based on demand, ensuring optimal performance and cost efficiency.
- Cost-effectiveness. You only pay for what you use.
- ECS manages both Linux and Windows containers, offering flexibility for diverse application needs.
- Monitoring and logging. ECS leverages Amazon CloudWatch for real-time monitoring and logging of containerized applications.
- Robust security. With ECS, you can assign granular permissions to each container, improving application isolation and security.
- Native support for most AWS services. For example, you can store and manage container images used by ECS through Amazon ECR (Elastic Container Registry). You can also distribute traffic across multiple containers for availability and reliability through Elastic Load Balancing (ELB).
- Additionally, ECS can run AI workloads in containers, optimizing the high-performance computing resources. It also supports multiple AI model deployments within a single environment, simplifying the management and scaling of AI services.
Amazon ECS limitations
ECS is built to run exclusively on AWS infrastructure, limiting its use in hybrid or multi-cloud environments. It also lacks an open-source community, restricting access to third-party tools and extensions.
Other ECS drawbacks include:
- Service quotas. ECS has default limits on services per cluster and tasks per service. These can be adjusted but may need management as workloads grow.
- Complex networking. Custom networking, especially with EC2 and awsvpc mode, can be challenging and demand careful handling of elastic network interfaces.
- API throttling. ECS enforces rate limits on API requests. This can impact large-scale deployments needing frequent API calls.
What Is Kubernetes?
Kubernetes (K8s) is an open-source container orchestration platform for running Linux containers.
Unlike Amazon ECS, Kubernetes is open-source and cloud-agnostic. It can be run on public clouds, private clouds, hybrid environments, or on-premises, thus avoiding vendor lock-in.
Kubernetes’ modular architecture offers flexibility and extensibility, enabling engineers to customize the platform to their application needs. Core components such as the API Server, Controller Manager, and Scheduler can be extended through custom resources and controllers, enabling Kubernetes to orchestrate diverse workloads, from basic setups to complex infrastructures.
Kubernetes also supports a range of plugins and extensions, including Custom Resource Definitions (CRDs), admission controllers, and network/storage plugins. These support deep customization, enabling users to integrate specialized hardware, enforce policies, or optimize configurations.
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Kubernetes benefits
Here are reasons to use Kubernetes:
- Kubernetes provides self-healing abilities. It restarts failed containers, replaces them, and kills containers that don’t respond to health checks.
- You can perform rolling updates and rollbacks. Update your applications without downtime and revert to a previous version if needed.
- Kubernetes offers horizontal scaling. Scale your applications up or down automatically based on demand to optimize resource usage.
- It has a large and active community. This means continuous improvements, a rich ecosystem of tools, and extensive support resources.
- Kubernetes supports declarative configuration. You define the desired state of your system, and Kubernetes works to maintain it, simplifying management.
- It includes built-in load balancing. Distribute network traffic evenly to maintain stable performance across your applications.
- Kubernetes supports secret and configuration management. It can securely store and manage sensitive information such as passwords and API keys.
- Kubernetes also supports a wide range of workloads. These include running stateless, stateful, and data-processing applications, making it versatile for different use cases.
Kubernetes limitations
A drawback of Kubernetes is its complexity. Setting up and managing a Kubernetes cluster requires specialized knowledge and can be resource-intensive. Even experienced teams may face steep learning curves, from configuring networking to managing security policies. This makes Kubernetes challenging for small teams or organizations new to container orchestration.
Other downsides of Kubernetes include:
- Kubernetes can be costly. Running and maintaining a Kubernetes environment at scale incurs significant infrastructure and operational costs. Learn how to optimize Kubernetes costs here.
- Resource consumption is high. Kubernetes demands substantial memory and CPU resources, which may lead to underutilized infrastructure and higher costs.
- Deployment times can be slow. While powerful, Kubernetes setups and updates are often complex, which may slow down rapid deployment cycles.
- Troubleshooting can be difficult. Debugging issues in Kubernetes, especially across distributed systems, can be complex.
ECS Vs. Kubernetes: Choosing The Right Container Service
|
Feature |
Amazon ECS |
Kubernetes |
|
Service type |
Fully managed container orchestration service by AWS |
Open-source container orchestration platform |
|
Vendor lock-in |
Tightly integrated with AWS services, primarily used within the AWS ecosystem |
Cloud-agnostic can be deployed on multiple cloud providers and on-premises |
|
Customization |
Limited to AWS features and integrations |
It is highly customizable with numerous plugins and extensions |
|
Deployment options |
Supports EC2 and Fargate launch types for container deployment |
Offers flexibility with various deployment strategies and tools |
|
Load balancing |
Uses AWS Elastic Load Balancer for distributing traffic |
Supports multiple load-balancing solutions, but requires additional setup |
|
Networking |
Integrated with AWS networking services such as VPC and ELB |
Requires configuration; supports various networking plugins |
|
Storage options |
Utilizes AWS storage services such as EBS and S3 |
Supports multiple storage solutions through Container Storage Interface (CSI) |
|
Monitoring and logging |
Integrated with AWS CloudWatch for monitoring and logging |
Requires third-party tools or additional setup for comprehensive monitoring |
|
Integration with other services |
Deep integration with AWS services like IAM, CloudWatch, and RDS |
Integrates with a wide range of third-party tools and services |
|
Security |
Leverages AWS IAM for access control and security policies |
Provides Role-Based Access Control (RBAC) and supports various security plugins |
|
Community and support |
Supported by the AWS community |
Large, active, open-source community with extensive resources |
AWS also offers Amazon Elastic Kubernetes Service (AWS EKS), a managed service that manages the process of running Kubernetes on AWS and on-premises.
Read our comprehensive guide on AWS EKS, how it works, and when to use it.
When To Use Amazon ECS Vs. Kubernetes
Choosing between Amazon ECS and Kubernetes depends largely on your container application needs. Here is when you would want to use Amazon ECS:
- Ideal if your applications are fully integrated within the AWS ecosystem, as ECS natively integrates with AWS services.
- Great for teams looking to deploy containers fast without complex configurations or extensive orchestration.
- Perfect for applications that need serverless containerization. AWS Fargate can manage the infrastructure automatically.
- Works well for teams looking to optimize costs within AWS, as ECS is tailored for cost-effective scaling on the platform.
On the other hand, Kubernetes will be a better option if you:
- Need portability and want to deploy across multiple cloud providers or on-premises envinronments.
- Run complex, stateful applications such as data-heavy or highly-customized workloads that require persistent storage.
- Need large-scale deployments with specific scaling configurations that go beyond what ECS provides.
- Need extensive customization.
- Want access to Kubernetes’s extensive community and tools, as well as frequent innovations and third-party integrations
Key Considerations: Cost, Scalability, And Maintenance
Additional factors to consider when choosing container solutions include:
Cost
Amazon ECS offers predictable pricing models tailored to AWS infrastructure. For example, ECS on Fargate uses a pay-as-you-go model, where you only pay for the exact resources you use (CPU, memory) without managing the servers themselves.
Amazon ECS pricing
- With EC2 Launch Type, costs include EC2 instance charges, storage, and any additional AWS services utilized.
- With the AWS Fargate Launch Type, You pay for the vCPU and memory resources your containers consume. For instance, Fargate pricing in the US East (N. Virginia) region is $0.04048 per vCPU per hour and $0.004445 per GB of memory per hour.
Here’s a complete breakdown of Amazon ECS pricing.
While open source and free to use, Kubernetes often calls for skilled DevOps personnel or managed services, as configuring and maintaining clusters across environments isn’t always straightforward. This can lead to higher operational costs for companies without in-house expertise.
However, its multi-cloud advantage also offers potential savings by shifting workloads to lower-cost providers or using hybrid setups for optimal performance and cost.
Kubernetes pricing
- Self-managed Kubernetes: Deploying Kubernetes on your own infrastructure involves costs for servers, storage, networking, and the personnel needed for maintenance and updates.
- Managed Kubernetes services: Cloud providers offer managed Kubernetes services with varying pricing:
- Amazon EKS: Charges $0.10 per hour per cluster, plus the cost of the underlying AWS resources. Read more on EKS pricing here.
- Google Kubernetes Engine (GKE): This service offers a Standard edition at $0.10 per cluster per hour and an Enterprise edition at $0.00822 per vCPU per hour. More on GKE pricing here.
- Azure Kubernetes Service (AKS): This service provides a free tier with no charge for cluster management and a Standard tier with additional features. See how to optimize AKC costs here.
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Scaling
Amazon ECS Service Auto Scaling automatically adjusts the number of tasks based on demand. This AWS-native scaling capability is seamless and enables users to specify scaling policies to match resource needs.
Kubernetes provides Horizontal Pod Autoscaling (HPA), a feature that adjusts the number of pods based on CPU or custom metrics. Kubernetes also supports custom and multi-dimensional scaling configurations, such as adjusting clusters across clouds or on-premises.
Maintenance
With ECS, there is minimal maintenance as AWS manages the underlying infrastructure, such as updates, security, and upkeep.
Kubernetes, however, demands hands-on management. Running it involves regular updates, security oversight, and resource monitoring, often relying on dedicated DevOps support.
Learn How To Optimize Amazon ECS And Kubernetes Costs With CloudZero
While containerization offers scalability and flexibility benefits, it also often incurs high costs due to overprovisioned resources, idle containers, and inefficient scaling. These factors inflate cloud bills without proper management, especially in complex deployments.
No matter your choice of container solution, CloudZero can help you optimize the costs.
How CloudZero optimizes ECS costs
- Tracks ECS spending in real-time, enabling teams to catch and address cost spikes immediately
- Identifies underused resources, supporting efficient rightsizing to cut unnecessary costs
- Recommends optimal EC2 instance types through CloudZero Advisor, ensuring cost-effective configurations
- Flags idle resources that may be inflating costs without contributing to performance
- Links costs to specific metrics such as cost per customer, teams, or projects, even with minimal tagging
How CloudZero optimizes Kubernetes costs
- Breaks down costs by cluster, namespace, pod, and label, offering a detailed cost view
- Combines Kubernetes costs with other cloud costs, simplifying budget management
- Tracks spending accurately, even with inconsistent or incomplete tags
- Provides hourly cost insights, unlike most platforms that update after 24 hours or more
- Highlights cost-saving opportunities across Kubernetes clusters, aiding informed decision-making
to see how it all works!
The Cloud Cost Playbook
The step-by-step guide to cost maturity
