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AWS ECS vs AWS Lambda: Top 5 Main Differences

Written By

Rodolfo Ortega

Cloud computing has revolutionized the software industry in the last 10 years. Today, most organizations prefer to host applications and services on the cloud due to ease of deployment, high security, scalability, and cheap maintenance costs over on-premise infrastructure. 

In 2006, Amazon launched its cloud services platform, Amazon Web Services (AWS), one of the leading cloud providers to date. Currently, AWS offers over 200 cloud services, including cloud hosting, storage, machine learning, and container management.

AWS Elastic Container Service (ECS) and AWS Lambda are both Amazon code deployment solutions, each with benefits and use cases. In this article, we will compare AWS ECS vs AWS Lambda, how each fulfills its function, and which of these is a better choice for your business requirements. 

Table of Contents 

AWS ECS Icon
AWS ECS Logo Icon

What Is AWS ECS

AWS ECS is a container management solution that manages and deploys docker containers. It treats each container as a task and provides users with the functionality to run, stop and manage them easily using the following components:

  • Task Definition: These define the configurations for a task. Users can apply a single definition to multiple tasks if required.
  • Tasks: An instance of a task definition is called a task. A task can be run standalone or as part of a service. In simple words, a task is a running container.
  • Cluster: Multiple running tasks form a cluster. A cluster can have multiple task definitions applied within them.

Essentially, containerization is a deployment technology that uses containers to store the entire application within an image file, including the code, all relevant installations, and operating system (OS) requirements. These files are very lightweight, easily deployable, and build the complete environment for the application to operate. Developers use containers to save themselves from the hassle of dependency issues and make deployments as smooth as possible.

Modern Microservices-based applications use containers for deployment. However, managing multiple containers becomes challenging, which means most companies opt for AWS ECS to streamline their container management needs. AWS ECS allows developers to deploy their containers using AWS Elastic Compute Cloud  (EC2) where the user has to maintain the EC2 infrastructure.

AWS ECS and AWS Fargate

AWS ECS can also be deployed via AWS Fargate. AWS Fargate is a new compute engine that automates the creation and management of the underlying infrastructure required to run containers. Fargate only requires users to upload the image to be deployed and select the CPU and memory requirements. The ease of deployment makes AWS Fargate a better choice for utilizing AWS ECS.

A key point to note is that AWS ECS solves the deployment issue for large-scale applications, but that may not always be what you are looking to manage. What if you need to deploy a small piece of code? Or a function that you need to execute with specific triggers? In this scenario, you can turn to AWS Lambda. 

AWS Lambda Icon
AWS Lambda Logo Icon

What is AWS Lambda?

AWS Lambda is a computing service that allows users to deploy small bits of code in a serverless environment where servers are managed entirely by the Cloud provider behind the scenes. It natively supports Java, Go, PowerShell, Node.js, C#, Python, and Ruby and provides a Runtime API that allows users to use any additional programming language. 

Functions defined in AWS Lambda run in an isolated environment, each having its separate resources and file system view. These functions are bound to triggers and are executed when certain events occur. For example, you can create a pre-processing function for images and store it on AWS Lambda. Now, whenever an image file is uploaded to the AWS S3 bucket, the function will be triggered, and the image will run through the algorithm before being uploaded. 

Other AWS Lambda triggers include:

  • Insert, update, and delete data Dynamo DB table
  • Modifications to objects in S3 buckets
  • Notifications sent from Amazon Simple Notification Service (SNS).

Another essential point to note is that AWS Lambda functions are executed in containers, which further helps with the isolation and security of the code. The appropriate runtime environment (Python, Node.js) is initialized within a container during execution. Once the execution is complete, the container is paused and resumed only for a subsequent call. The AWS runtime deletes the container if no call is made during a specific period, and after that, a new container must be initialized.

AWS ECS vs AWS Lambda: What are the Differences?

Both services help clients deploy applications and code, but both have very different use cases. It is important to explore these differences to understand which of the two best suits your requirements.

The table below outlines a side-by-side comparison of AWS ECS vs AWS Lambda:

AWS ECS AWS Lambda
High-performing and scalable container management service A function-executing service that runs in response to triggers, powered by a serverless environment.
Only works with containers. All you need to do is point to a container registry with your Docker image and the rest is managed by the service. Only requires you to write the code. Currently, AWS Lambda supports Python, NodeJS, Java, Ruby, GO, C# and Powershell.
Used for running Docker containers and deploying entire enterprise-scale applications. Used for a small application built with a few lines of code.
The tasks can be run for a long time and task count can be scaled by integration with Amazon CloudWatch alarms. The Lambda function execution time is limited to 15 minutes.
The running EC2 Clusters are charged by the hour, which means they are more costly.  AWS Fargate costs start at about $0.04 vCPU per hour. AWS Lambda is billed based on the number of requests to the more cost-effective function.

There is no clear winner as both services seem to benefit different domains. However, there are a few key takeaways from the comparison:

  • AWS ECS is built to handle large applications and offers scalability, while AWS Lambda enjoys rapid execution of code to perform important runtime tasks. 
  • Cost is another important factor, and AWS Lambda wins here since you only pay for the processing power used while running Lambda functions.

To make an informed decision, you first need to explore your business requirements.

AWS ECS vs AWS Lambda: How To Choose

When choosing amongst the services mentioned above, the following questions can help clarify the decision:

  • What is the size of my application?

Large-scale applications would be unmanageable on AWS Lambda, therefore, AWS ECS is the better choice.

  • What is the run time of my application?

AWS Lambda limits program execution to 15 mins, so if the application is to run for a longer time, AWS ECS is a better choice.

  • What is my software development and deployment budget?

Both services seem a good fit in their respective scenarios, but AWS  Lambda’s cheaper pricing structure gives it an edge over AWS ECS.

  • What are my project configuration requirements?

As easy as it is, AWS ECS still has more setup requirements than AWS Lambda but it offers greater configuration flexibility. In contrast, AWS Lambda is the better choice if you want a program executed straight away with minimal configuration.

These questions should help in making a better decision in choosing a deployment service between AWS ECS vs AWS Lambda. 

Conclusion

If you use Amazon Web Services, it is likely that you currently use at least one of these core AWS features. The benefits they provide may seem to overlap sometimes. But each service has unique capabilities that you may want to use in some cases and not so much in others. 

This perspective is reinforced by our detailed AWS ECS vs AWS Lambda comparison where it is evident that the former is suitable for large-scale applications while the latter works better when you need rapid execution of code to perform important runtime tasks.

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