Top Mistakes to avoid when using AWS ECS to manage containers in 2023

Amazon has been doing a great job of maintaining ECS and adding new features. Unfortunately, this means that it’s getting more complicated to use as well. As a result, there are a number of common mistakes that people make when using AWS ECS to manage containers in their cloud-based applications.

Don’t use AMIs

One of the most important things to remember is that you should not use AMIs. If you do, your container will not be able to scale up and down. Instead, you need to use ECS-optimized AMIs. This can be done with the AWS CLI or AWS CloudFormation templates (which are templates for creating your infrastructure on AWS).

To check if your task definition uses an ECS-optimized AMI, run the following command:

aws ecs validate — cli-input-json file:///tmp/minikube_ecs_validation_output.json

If validation fails, it means either there is no agent installed on one or more of your host instances, or there is no agent running at all (for example, because it crashed). In this case, check if there are any errors in the logs related to starting/stopping agents and try again with a different configuration until everything works as expected!

Don’t assume you have enough capacity to run your tasks

You need to understand how many containers you can run on your cluster. This is a first step because it will help you determine how many tasks are needed to be scheduled to run in a given time frame. For example, if your cluster has 1 TB of memory and runs at 50% CPU utilization, it is possible that you could run 10,000 tasks per hour (assuming no other limitations).

However, there are also limitations introduced by task scheduling policies and limits on container sizes which require additional consideration. For example, some policy types may limit the number of tasks that can be scheduled per instance or the maximum number of instances in a cluster (and therefore the total capacity available for running containers). Additionally, constraints such as limits on disk space might prevent certain applications from being deployed using ECS resources effectively

Don’t make a one-size-fits-all task definition

One of the most important things to remember is that a task definition is not the same thing as a container. A task definition is an instruction set for creating and managing containers. It describes how much memory, CPU, disk space and other resources each task should receive. The container itself does not have any persistent storage or state information in it; all that stuff gets stored in ECS services (or in AWS if you’re using the Fargate (EC2 Container Service option).

Tasks are assigned to containers based on their requirements — you can’t assign more than one instance of a particular container type to a single task unless they’re identical in size, configuration etc..

Don’t assume anything about the order containers will be started in.

When you don’t specify an order, ECS will start the containers in a random order. If you want to ensure that the containers start in a particular order, you can define a task definition with a task execution strategy of “Ordered”. Then, when you use that task definition for one or more tasks and start those tasks, ECS will execute them in the order specified by your task definitions.

If you’re using an existing container image from another registry (e.g., Docker Hub), it may not be possible for you to change their base images until they are updated on Docker Hub again — and even then it might not be easy if there are other dependencies from other repositories involved (e.g., Kubernetes). However, if all of your container images can be rebuilt without breaking any dependencies (e.g., if they have no runtime packages installed), then rebuilding them is an option worth considering because it provides some level of protection against future updates breaking things unexpectedly!

Don’t forget to add a command attribute to your task definitions.

One of the most commonly forgotten attributes is command. This attribute tells ECS what command will be run in your container. If you don’t specify this value, it will run nothing! You can use any valid shell script or executable for this value, but you must include it.

For example, if I wanted to run a shell script named update-hosts that would add my internal DNS servers into /etc/hosts on my Linux host machine when I launched a task from ECS (which has Docker installed), then I would create a task definition like so:

```javascript

{ “family”: “myApp”, “instanceType”: “t2.medium”, “command”: “/home/ubuntu/update-hosts” }

```

Don’t assume that resources limits or requests are static.

You should never assume that your resources limits are static, or that you can use more resources than you have requested. Likewise, you should not make assumptions about the amount of resources that will be available in the future. Amazon Web Services (AWS) provides a variety of tools for managing these types of issues, but it’s up to you to know when and how to use them.

Don’t try to manually deploy container images

One of the most common mistakes made by organizations who are new to using AWS ECS is trying to deploy container images manually. This involves uploading container images from your local machine into Amazon Elastic Container Registry (ECR) or Docker Hub and then creating a service with the image as its source.

Instead, you should use either Docker CLI or AWS ECR directly so that you can take advantage of automated processes for building and transferring your container images, rather than relying on manual actions. You’ll want these steps to be automated because they will help ensure that your deployment processes don’t fail due to human error or other issues. If this sounds overwhelming, remember that all the tools required are available in public repositories such as GitHub and Docker Hub; they just need to be installed on your system before you begin using them!

AWS ECS is tricky and getting trickier, so pay attention.

The AWS ECS service is a complex system and getting more so, albeit in ways that you might not be aware of. As you’re getting started, it’s important to understand what AWS ECS does for you and how it can help — and where it falls short.

If your team is using containers, then ECS has a lot of good things going for it:

• It integrates with other AWS services (like S3 or RDS), which makes managing containers much easier than installing software on-premise or using an open source container management system like Kubernetes or Mesos. * It offers built-in high availability (HA) support, which means that if a worker instance fails, another instance will take over the workload automatically.
• You can use Auto Scaling Groups (ASG) to scale up the number of instances based on demand; ASG also integrates well with other AWS services like CloudWatch alarms so that your application responds accordingly when there’s an increase in traffic or new features go live.* The newest version includes native integration with ReactiveCocoa and RxSwift frameworks.* You can also integrate directly with Lambda functions via custom runtimes called “Fargate” which eliminates infrastructure management altogether!

Conclusion

AWS ECS is a powerful tool for managing containers, but it’s not perfect. To get the most out of it in 2023 and beyond, be sure to avoid these common mistakes so that you can use AWS ECS as efficiently as possible!