Data Intellect
Containers have revolutionised the way applications are deployed and managed. By bundling everything an application needs to run (its code, libraries, and dependencies), containers ensure a consistent environment across different systems. This approach simplifies development, improves scalability, and enhances portability. However, managing containers at scale can be challenging without the right orchestration tools. This is where AWS Elastic Container Service (ECS) comes in, offering a fully managed way to deploy, scale, and maintain containerised applications.
In this post, we’ll explore why ECS is an excellent choice for containerised deployments, its architecture, key benefits, and how to get started.
For information on setting up initial containers for development locally, click on the button below to read our previous blog.
Traditionally, hosting a container requires setting up and maintaining your own servers, configuring networking, managing port mappings, and handling scaling concerns. This infrastructure management overhead can slow down development cycles and introduce complexity.
AWS ECS eliminates these challenges by providing a fully managed orchestration service that takes care of infrastructure provisioning, networking, scaling, and load balancing. Instead of worrying about managing virtual machines, ECS allows you to focus purely on your application’s logic.
One of the biggest concerns for any application is how it handles unpredictable traffic patterns. Whether it’s a seasonal sales rush or an unexpected surge in users, scaling infrastructure manually can be inefficient and costly.
ECS solves this problem by offering auto-scaling capabilities. It dynamically adjusts the number of running containers based on demand, ensuring that applications remain responsive under any traffic load. Instead of provisioning excess capacity upfront (which increases costs), ECS allows businesses to scale up when needed and scale down when demand drops, optimizing resource usage.
Containers are designed to be portable, meaning they can run in any environment that supports containerization. Whether you’re deploying to AWS, an on-premises data center, or a hybrid cloud environment, ECS makes it easy to maintain application consistency across different platforms.
By using AWS Elastic Container Registry (ECR) alongside ECS, teams can manage container images seamlessly across multiple regions, ensuring high availability and quick deployments without compatibility issues.
Downtime is costly, both in terms of revenue and user experience. ECS helps prevent service disruptions by ensuring high availability through automatic container recovery. If an individual task fails, ECS detects the issue and automatically restarts it to maintain the desired number of running tasks.
Additionally, ECS integrates with AWS services like Elastic Load Balancing (ELB) to distribute traffic across multiple containers, reducing the risk of overload on any single instance. This ensures that your application remains resilient, even in the face of unexpected failures.
One of the major benefits of using ECS is its seamless integration with other AWS services. Need to monitor application performance? Use Amazon CloudWatch. Want to enforce security policies? Leverage AWS Identity and Access Management (IAM). Looking to set up a secure private network for your containers? Use Amazon VPC (Virtual Private Cloud).
Since ECS is deeply embedded within the AWS ecosystem, it enables a frictionless experience when connecting to services like S3, DynamoDB, and RDS, making it easier to build and operate cloud-native applications.
Traditionally, businesses had to over-provision hardware to handle peak loads, leading to wasted resources during off-peak hours. With ECS, you only pay for the compute resources your containers consume. Whether you’re using AWS Fargate (a serverless option) or EC2-backed ECS clusters, you can optimise costs based on workload requirements.
Additionally, with auto-scaling in place, ECS ensures that businesses do not overpay for unused resources, making it a cost-effective solution for organizations of all sizes.
Rolling out new application versions can be risky. A bad deployment could lead to downtime or system failures. ECS mitigates this risk by supporting blue-green deployments, where a new version of an application is deployed alongside the existing one.
This allows teams to gradually shift traffic to the new version, monitor its performance, and roll back instantly if issues arise. Combined with AWS CodeDeploy, ECS makes deployment strategies more reliable and reduces the impact of failed updates.
AWS ECS consists of two primary components:
ECR (Elastic Container Registry), which is a repository to store, manage, and retrieve Docker images, and ECS (Elastic Container Service), a container orchestration service that runs and manages your containers.
ECS is built on four key concepts:
– Task Definition: A blueprint that defines the resources required for your container (CPU, memory, ports, volumes, etc.).
– Task: A running instance of a task definition.
– Service: Ensures tasks remain running and restarts them if needed.
– Cluster: A logical grouping of resources where containers run.
You have an ECS cluster, that holds your services. A running instance of that service is a task, and belonging to that task is a task definition, which defines the resources your container is allowed to use, as well as referencing the container image link that is hosted on ECR.
Additionally, security groups and IAM roles manage access control, ensuring secure deployment and integration with other AWS services like logging and monitoring.
ECR stores your Docker images and makes them accessible for ECS deployment. Create a repository for versions of your container image.
Use a Dockerfile to define the environment your application needs, ensuring necessary dependencies and ports are exposed.
$ docker build -t my-app:latest ./Dockerfile
$ docker tag my-app:latest <aws_account_id>.dkr.ecr.<region>.amazonaws.com/my-app:latest
$ docker push <aws_account_id>.dkr.ecr.<region>.amazonaws.com/my-app:latest
Set up an ECS cluster where your containers will run.
Reference your ECR image and specify resource requirements, including port mappings for web applications.
{
"requiresCompatibilities": [ "FARGATE" ],
"family: "",
"containerDefinitions": [
{
"name": "MY-APP",
"image": "ecr_url/MY-APP-IMAGE:LATEST",
"essential": true
}
],
"volumes": [],
"networkMode": "awsvpc",
"memory": "3 GB",
"cpu": "1 vCPU",
"executionRoleArn": "arn:aws:iam::ACCOUNT:role/executionRole"
}
Deploy your task definition within the ECS cluster to ensure continuous operation and scalability.
Your service is now running on ECS Fargate, and will be resilient enough to add scaling tools, and restart itself on error to minimise downtime.
Amazon’s ECS makes containerised deployments simple, scalable, and cost-effective. By leveraging managed services like ECS and ECR, teams can focus on building applications instead of managing infrastructure. Whether you need to process continuous data streams, deploy scalable microservices, or run web applications with exposed ports, ECS provides a robust and flexible solution. You can further enhance development cycles with code repository pipeline tools to automate these steps for one click deployments. As part of our CI/CD work we have automated many of these steps in a bitbucket-pipelines file. Including building, tagging and pushing images dynamically (through Docker), as well as defining the appropriate AWS resources (with Terraform). Whilst this is good practice for working in a larger team, the steps outlined above provide a good entry point.
With features like auto-scaling, service persistence, seamless rollbacks, and integration with AWS’s powerful ecosystem, ECS is an excellent choice for modern application deployments, and is sure to streamline your CI/CD pipelines to create a more efficient development cycle.
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