A Beginner‘s Guide to Amazon‘s Elastic Container Service (ECS)

Amazon‘s Elastic Container Service, or ECS for short, is a powerful yet easy way to run Docker containers at scale in the cloud. In this beginner‘s guide, we‘ll dive into what ECS is, why you might use it, its core concepts and architecture, and walk through a simple tutorial to get you up and running with your first containerized application on ECS.

The Rise of Containers

Before we jump into ECS, it‘s important to understand the technology that underpins it – containers. Containers provide a standard way to package your application‘s code, configurations, and dependencies into a single object. Containers are an abstraction at the app layer that packages code and dependencies together.

Multiple containers can run on the same machine and share the OS kernel with other containers, each running as isolated processes in user space. Containers take up less space than VMs (container images are typically tens of MBs in size), and start almost instantly.

This allows developers to create predictable environments that are isolated from other applications. Containers can be used in development to maintain consistent environments and easily shared with team members. They are also ideal for microservices architectures since containers are portable, efficient and can be easily orchestrated.

The most popular container runtime is Docker. Docker allows you to automate the deployment of applications inside software containers. Using Docker, you can define what goes in a container, share containers with your team, and deploy containers to servers.

Enter Container Orchestration

While Docker makes it easy to build, ship and run containers, managing them at scale still presents challenges. How do you automate container deployment and scaling? How do you enable containers to discover and talk to each other? How do you manage their lifecycles, handle failures and perform updates without downtime?

This is where container orchestration platforms come in. Container orchestration automates the deployment, management, scaling, and networking of containers. Orchestration makes it easy to manage a cluster of machines running containers.

Some of the popular container orchestration tools include:

• Kubernetes: The most popular open-source platform for container orchestration originally developed by Google. It provides a platform to configure, automate and scale containers.

• Docker Swarm: Docker‘s native orchestration engine that turns a pool of Docker hosts into a single virtual host. It provides a declarative way to define applications and comes bundled with Docker.

• Apache Mesos: An open-source project to manage computer clusters, Mesos is suited for very large deployments but has a steeper learning curve.

And of course, Amazon ECS, which we‘ll dive into next. While you can run these other orchestrators on AWS infrastructure, ECS provides a native experience to run containers on AWS without having to manage the control plane yourself.

Introducing Amazon ECS

Amazon Elastic Container Service (Amazon ECS) is a fully managed container orchestration service that makes it easy for you to deploy, manage, and scale containerized applications. It deeply integrates with the rest of the AWS platform to provide a secure and easy-to-use solution for running container workloads in the cloud.

With Amazon ECS, you can use API calls to launch and stop Docker-enabled applications, query the complete state of your cluster, and access many familiar Amazon EC2 features. You can use Amazon ECS to schedule the placement of containers across your cluster based on your resource needs and availability requirements.

ECS eliminates the need for you to install, operate, and scale your own cluster management infrastructure. It is well-suited for long-running applications and services like web apps and backend APIs. For short-running batch jobs, AWS also offers AWS Batch.

Some key benefits of using Amazon ECS:

• Orchestrate containers at scale without managing servers
• Deep integration with AWS services like Elastic Load Balancing, VPC, IAM
• Security and isolation by design
• Easy portability from dev to test to production
• Flexible options with both EC2 and AWS Fargate launch types

ECS Core Concepts

To use ECS, it‘s important to understand a few key concepts:

• Cluster: An ECS cluster is a logical grouping of tasks or services. You can register one or more EC2 instances (also referred to as container instances) with your cluster to run tasks on them.

• Task Definition: A task definition is like a blueprint that describes one or more containers (up to a maximum of ten) that form your application. You can think of it as a multi-container Dockerfile.

• Task: A task is an instantiation of a task definition that is running on a container instance within your cluster. Based on the task definition, ECS will launch the specified containers on a container instance.

• Service: An ECS service allows you to run and maintain a specified number of instances of a task definition simultaneously in an ECS cluster. If a task fails or stops, the ECS service scheduler launches another instance based on the task definition.

• Container Agent: The ECS container agent runs on each container instance within an ECS cluster. It sends information about the resource‘s current running tasks and resource utilization to Amazon ECS, and starts and stops tasks whenever it receives a request from Amazon ECS.

Here‘s a high-level architecture diagram showing how the pieces fit together:

[ECS Architecture Diagram]

In this example, we have an ECS cluster with two container instances registered. The cluster is running two services – a frontend web service and a backend API service. Each service has a task definition specifying which container images to use and resource requirements. The services are scaled out to run multiple tasks across the available container instances in the cluster.

Getting Started with ECS

Now that you have an understanding of ECS concepts, let‘s walk through deploying a simple web application on ECS. We‘ll use the Amazon ECS first-run wizard in the AWS Management Console, which simplifies the process of creating a cluster and launching a containerized application.

Prerequisites:

• An AWS account
• The AWS CLI installed and configured with IAM credentials
• A Docker image of your application pushed to a registry like Amazon ECR or Docker Hub

Step 1: Open the Amazon ECS console, choose "Clusters" and click "Create Cluster".

Step 2: On the cluster template selection page, choose "EC2 Linux + Networking" and click Next. This will use the EC2 launch type, as opposed to AWS Fargate.

Step 3: Configure your cluster by entering a name and choosing EC2 instance type, number of instances, VPC and subnet settings. You can leave the other settings as default. Click Create.

This will launch EC2 instances in your account, install the ECS container agent on them, and register them to a new ECS cluster.

Step 4: Once your cluster is provisioned, click "View Cluster" and then choose the "Tasks" tab followed by "Run new Task".

Step 5: On the task definition page, select "Create new Task Definition" and enter a name. Click "Add container" and specify your container image URL, memory/port settings. Click "Add" and then "Create".

Step 6: Choose your newly created task definition, the number of tasks to launch, cluster VPC/subnet settings and click "Run Task". ECS will then pull your container images and deploy them as tasks in your cluster.

Congratulations! You now have a containerized application running on ECS. The tasks are distributed across the EC2 instances in your cluster. ECS automatically handles scheduling, placement and recovery of containers.

To expose your application to the internet, you can configure an Application Load Balancer and target group to direct traffic to the dynamic ports used by your tasks.

ECS Best Practices

As you move to running production workloads on ECS, there are a few best practices to keep in mind:

Use services: For long-running, scalable applications, always deploy them as ECS services to maintain a desired task count.

Separate clusters: Use separate ECS clusters for development, testing and production environments. This provides isolation between workloads and enables blue/green deployments.

Enable CloudWatch monitoring: Monitor key metrics for your ECS cluster, services and tasks using Amazon CloudWatch. Create alarms to notify you of any issues.

Implement auto scaling: Automatically adjust the desired count of tasks in your ECS service based on metrics like CPU and memory utilization. This ensures optimal performance and cost.

Secure your infrastructure: Run your containers in a private VPC, use IAM roles for tasks to control access to other AWS resources, and encrypt data at rest and in transit.

Implement CI/CD: Automate your container build, test and deployment workflow using services like AWS CodePipeline, AWS CodeBuild and AWS CodeDeploy. This enables reliable and faster release cycles.

These are just a few considerations as you adopt containers and ECS at scale. Continually monitor and iterate on your architecture to identify bottlenecks and opportunities to optimize for performance, cost, and reliability.

ECS Pricing

With Amazon ECS, there are no upfront fees or commitments. You pay only for the AWS resources (e.g. EC2 instances or EBS volumes) you create to store and run your application.

EC2 launch type: With EC2 launch type, you explicitly provision EC2 instances to serve as container hosts in your ECS cluster. You are responsible for patching and scaling the instances. The EC2 instances you run will be billed based on their size and the prices published on the EC2 pricing page.

Fargate launch type: With Fargate launch type, you do not have to provision any infrastructure. You specify your container resource requirements and Fargate automatically launches containers for you. Fargate pricing is calculated based on the vCPU and memory resources used from the time you start to download your container image until the task terminates.

ECS also provides a pricing calculator to estimate your monthly bill based on projected usage.

Conclusion

Amazon ECS is a powerful platform that makes it easy to deploy, manage, and scale Docker containers on AWS. Its deep integration with other AWS services provides a complete solution for running containerized applications in the cloud.

In this guide, we covered the fundamentals of containers and container orchestration, core ECS concepts like clusters and task definitions, and how to deploy your first containerized application on ECS. We also touched upon ECS pricing and some architectural best practices to consider.

From here, you can dive deeper into more advanced ECS concepts like service auto scaling, blue/green deployments, service discovery, and integrating with other AWS services like AWS Lambda and Amazon RDS.

Check out these resources to continue your ECS learning journey:

• Getting Started with Amazon ECS
• ECS Workshops
• Containers from the Couch video series
• Deploying Microservices with Amazon ECS (re:Invent session)

The move to microservices and cloud-native architectures is pushing the adoption of containers and container orchestration. Platforms like Amazon ECS provide the right level of abstraction and automation to deploy containers at scale without managing infrastructure yourself.

Happy containerizing!