AWS offers a broad spectrum of compute offerings that give you the flexibility to choose the right tool for the job. The three main categories of compute are virtual machines (VMs), containers, and serverless. No one-size-fits-all compute service exists because it depends on your needs.
The key is to understand what each option offers. Then you can build an appropriate cloud architecture for your use case. In this section, you will learn about containers and how to run them.
Containers can host a variety of different workloads, including web applications, lift and shift migrations, distributed applications, and streamlining of development, test, and production environments.
Containers
A container is a standardized unit that packages your code and its dependencies. This package is designed to run reliably on any platform, because the container creates its own independent environment. With containers, workloads can be carried from one place to another, such as from development to production or from on-premises environments to the cloud.
An example of a containerization platform is Docker. Docker is a popular container runtime that simplifies the management of the entire operating system stack required for container isolation, including networking and storage. Docker helps customers create, package, deploy, and run containers.
Difference between VMs and containers
Containers share the same operating system and kernel as the host that they exist on. But virtual machines contain their own operating system. Each virtual machine must maintain a copy of an operating system, which results in a degree of wasted resources.
A container is more lightweight. Containers spin up quicker, almost instantly. This difference in startup time becomes instrumental when designing applications that must scale quickly during I/O bursts.
Containers can provide speed, but virtual machines offer the full strength of an operating system and more resources, like package installation, dedicated kernel, and more.
Orchestrating containers
In AWS, containers can run on EC2 instances. For example, you might have a large instance and run a few containers on that instance. Although running one instance is uncomplicated to manage, it lacks high availability and scalability. Most companies and organizations run many containers on many EC2 instances across several Availability Zones.
If you’re trying to manage your compute at a large scale, you should consider the following:
How to place your containers on your instances
What happens if your container fails
What happens if your instance fails
How to monitor deployments of your containers
This coordination is handled by a container orchestration service. AWS offers two container orchestration services: Amazon Elastic Container Service (Amazon ECS) and Amazon Elastic Kubernetes Service (Amazon EKS).
Managing containers with Amazon ECS
Amazon ECS is an end-to-end container orchestration service that helps you spin up new containers. With Amazon ECS, your containers are defined in a task definition that you use to run an individual task or a task within a service. You have the option to run your tasks and services on a serverless infrastructure that's managed by another AWS service called AWS Fargate. Alternatively, for more control over your infrastructure, you can run your tasks and services on a cluster of EC2 instances that you manage.
If you choose to have more control by running and managing your containers on a cluster of Amazon EC2 instances, you will also need to install the Amazon ECS container agent on your EC2 instances. Note that an EC2 instance with the container agent installed is often called a container instance. This container agent is open source and responsible for communicating to the Amazon ECS service about cluster management details. You can run the agent on both Linux and Windows AMIs.
When the Amazon ECS container instances are up and running, you can perform actions that include, but are not limited to, the following:
Launching and stopping containers
Getting cluster state
Scaling in and out
Scheduling the placement of containers across your cluster
Assigning permissions
Meeting availability requirements
To prepare your application to run on Amazon ECS, you create a task definition. The task definition is a text file, in JSON format, that describes one or more containers. A task definition is similar to a blueprint that describes the resources that you need to run a container, such as CPU, memory, ports, images, storage, and networking information.
Here is a simple task definition that you can use for your corporate directory application. In this example, this runs on the Nginx web server.
{
"family": "webserver",
"containerDefinitions": [ {
"name": "web",
"image": "nginx",
"memory": "100",
"cpu": "99"
} ],
"requiresCompatibilities": [ "FARGATE" ],
"networkMode": "awsvpc",
"memory": "512",
"cpu": "256"
}
Using Kubernetes with Amazon EKS
Kubernetes is a portable, extensible, open-source platform for managing containerized workloads and services. By bringing software development and operations together by design, Kubernetes created a rapidly growing ecosystem that is very popular and well established in the market.
If you already use Kubernetes, you can use Amazon EKS to orchestrate the workloads in the AWS Cloud. Amazon EKS is a managed service that you can use to run Kubernetes on AWS without needing to install, operate, and maintain your own Kubernetes control plane or nodes. Amazon EKS is conceptually similar to Amazon ECS, but with the following differences:
In Amazon ECS, the machine that runs the containers is an EC2 instance that has an ECS agent installed and configured to run and manage your containers. This instance is called a container instance. In Amazon EKS, the machine that runs the containers is called a worker node or Kubernetes node.
An ECS container is called a task. An EKS container is called a pod.
Amazon ECS runs on AWS native technology. Amazon EKS runs on Kubernetes.
If you have containers running on Kubernetes and want an advanced orchestration solution that can provide simplicity, high availability, and fine-grained control over your infrastructure, Amazon EKS could be the tool for you.