Fargate vs Lambda: Which Serverless Solution is the Right Fit For You?

Fargate vs Lambda: Summary Insights

Table of Contents

What is AWS Fargate?

AWS Fargate is a serverless service that lets you run containers without having to manage the underlying infrastructure. It works with both Amazon ECS and EKS. With Fargate, you don’t have to worry about selecting server types, scaling, or managing containers. All you need to do is choose the CPU and memory your app requires, set up networking and security rules, and launch your app. Also, Fargate is a robust choice for containerized workloads, especially when paired with the right AWS monitoring tools to ensure performance reliability.

Key Features of Fargate:

• Event-driven Execution: Fargate runs your container apps only when needed, based on the resources you set.
• Automatic Scaling: Fargate changes the number of containers as needed, and you only pay for what you use.
• Works with ECS and EKS: Fargate works with ECS for Docker containers or EKS for Kubernetes.
• No Server Management: You don’t have to manage servers, making running and updating your container apps easier.

How Fargate Works

• Start by defining your application: Create containers using task definitions in ECS or pods in EKS. You’ll need to specify details like the container image, required CPU and memory, network settings, and roles for tasks or services.
• Next, set up the task definition: After defining the application, set up the task or pod that will run. This step ensures that all the necessary resources and settings are ready.
• Next, run the task: You can start the tasks either by hand or automatically. Each task or pod runs in its isolated environment, so it doesn’t share resources with others.
• Finally, let Fargate manage resources: Fargate automatically provides the compute resources for your application. It also scales your tasks, adding more when needed and reducing them when fewer resources are required.

What is AWS Lambda?

AWS Lambda is a serverless service that lets you run code without having to manage servers. Unlike AWS Fargate, Lambda automatically adjusts by running specific code, called a serverless function, whenever an event happens. It handles each event individually and scales depending on the workload.

With Lambda, deploying an application is as easy as writing and uploading a function. You only pay for the time your code is running, and there are no charges when it’s not. You can set up triggers from other AWS services or call the function directly from websites or mobile apps.

Key Features of Lambda:

• Event-Driven Execution: Lambda executes your code automatically when specific events occur, such as uploading a file or making an API request.
• Supports Multiple Languages: You can write your Lambda functions using programming languages like Python, Java, Node.js, or Go.
  Automatic Scaling: Lambda automatically adjusts the number of code copies depending on traffic or demand.
• No Server Management: AWS handles server management, updates, and monitoring, so you just focus on writing your code.

How AWS Lambda Works

• Write Your Code: First, write your code in any supported language and save it as a ZIP file. This file is known as a Lambda function.
  Upload Your Code: Upload the ZIP file to AWS Lambda, where your code will be stored.
• Set Triggers: You can set up your function to run automatically when specific events happen, like a new file uploaded to Amazon S3 or a new record added to DynamoDB. This can also be triggered by HTTP requests through Amazon API Gateway.
• Execution on Demand: Lambda automatically runs your function on the required infrastructure when an event happens. It handles your server and system management, scaling, and monitoring.
• Automatic Scaling: If your function is already running when another event occurs, Lambda will launch a new instance of your function to handle the event, automatically scaling based on the number of events.

AWS Fargate vs Lambda: Table of Difference

Fargate vs Lambda: In-Depth Differences You Should Know

1. Compute Model

When comparing Fargate vs Lambda for computing needs, Fargate lets you run containers without managing the underlying servers. You can use Docker containers, and Fargate takes care of everything behind the scenes, so you don’t need to manage the infrastructure. You define the computing resources needed, including CPU and memory, and Fargate provides and scales for you. While Lambda gives you more control over the application environment, Fargate focuses on containers and their needed resources.

On the other hand, Lambda is a service offering server-less computing support for multiple programming languages. You upload your code, which is called an “application function,” and AWS runs it for you when something happens, like an API call or a file upload. It runs your code only when needed and changes the resources based on the amount of work.

2. Provisioning and Management

When comparing AWS Fargate vs Lambda for provisioning and management,Fargate abstracts away infrastructure management like Lambda, but you still define container configurations such as CPU, memory, and storage. It’s suitable for workloads that require the flexibility of containerization while avoiding the need to manage EC2 instances.

On the other hand, Lambda is entirely serverless, meaning AWS manages all provisioning, scaling, and infrastructure aspects. Simply upload your code, and AWS will run and scale it as events occur. There’s no need to worry about managing containers, servers, or hardware.

3. Scalability

When comparing Fargate vs Lambda for scalability, Fargate offers the ability to adjust resources by adding or removing instances based on your application’s needs.AWS manages the infrastructure, so you don’t have to worry about it, giving you more control over your application’s scaling.

In contrast, Lambda automatically scales depending on the number of events or requests it has to process. It adjusts its capacity quickly to maintain consistent performance while minimizing costs. You don’t need to plan or manage the capacity—Lambda takes care of scaling up or down, allowing you to focus more on writing your code than managing infrastructure.

4. Cost Model

When comparing AWS Fargate vs Lambda for pricing, AWS Fargate charges based on your containers’ CPU and memory resources. You pay for the time your containers are running. This model is more affordable for long-running applications but may not be as cost-effective for short tasks.

AWS Lambda uses a pay-as-you-go model. You’re only charged for the time your code runs (measured in milliseconds) and the memory it uses. There are no initial costs, just payment for the actual execution time. Also, leveraging AWS Auto Scaling can optimize costs, particularly for Fargate workloads that handle fluctuating traffic demands.

5. Pricing

• AWS Fargate
When comparing Fargate vs Lambda for pricing, AWS Fargate charges per second based on your containerized apps’ resources, such as CPU, RAM, storage, and OS.

• Charges are calculated from the start of the container image download until the task ends, with a one-minute minimum charge (15 minutes for Windows containers).
• Pricing varies by region (e.g., US East: $0.04048/vCPU/hour and $0.004445/GB/hour).

• Note: Extra charges for data transfers and AWS services such as CloudWatch Logs may apply.

Savings: You can save with AWS Savings Plans (up to 50%) or Fargate Spot (up to 72%).

• AWS Lambda
Here Lambda doesn’t charge based on server units. Instead, it charges for two things:
1. Number of Requests: You are charged every time AWS Lambda starts running your function in response to an event or trigger.
2. Execution Time: You are also charged for how long your function takes to execute, measured in milliseconds. The billing starts when your function begins and ends when it finishes.

Lambda charges are based on 1-millisecond intervals. The cost varies depending on how much memory you assign to your function—more memory means higher costs.

Provisioned Concurrency: If you enable this feature, Lambda will charge you based on the amount of concurrency (how many requests your function can handle at once) and how long it’s active.

Also, if you run Lambda functions on Graviton2 processors (using AWS’ Arm architecture), you could save up to 34% compared to standard processors for tasks like data processing, media work, and web backends.

6. Performance

When comparing AWS Fargate vs Lambda for performance, Fargate offers consistent performance because each task has its own dedicated resources. This means your CPU, memory, and storage are not shared with other tasks, ensuring stable and reliable performance for your application.

The performance of Lambda depends on the amount of memory you assign to your functions.
The more memory you provide, the more CPU power, network speed, and disk resources your function gets. This makes adjusting your Lambda functions’ cost and performance simple based on what you need.

7. State Management

When comparing Fargate vs Lambda for state management, Fargate allows you to use containers that can retain state as long as you configure the persistent storage (e.g., leveraging Amazon EFS or other storage solutions). Containers can hold data for longer durations, making Fargate a better choice for stateful applications than Lambda.
Lambda is stateless, meaning it does not store data between invocations. If your application needs to retain state or data, use external storage services like S3, DynamoDB, or RDS.

8. Deployment and Management

When comparing AWS Fargate vs Lambda for deployment and management, Fargate allows you to deploy containerized applications using Docker images. You can use services like Amazon ECS or Amazon EKS (Elastic Kubernetes Service) to deploy and manage containers. Fargate integrates with CI/CD tools for automated deployments, making it suitable for containerized microservices and applications.

Lambda functions are deployed by uploading the code through the AWS Console, CLI, or SDKs. Deployments can be managed through CI/CD pipelines using tools like AWS CodePipeline. Lambda works with event-based systems and connects with other AWS services to simplify workflows.

9. Security

When comparing Fargate vs Lambda in terms of security, Fargate handles much infrastructure security, but security permissions are tied to the containers or pods where your tasks run. Each task in Fargate has its isolated environment, meaning it does not share resources like CPU, memory, or network with other tasks. For better app security, you can integrate Fargate with AWS Secret Manager or Systems Manager Parameter Store to manage sensitive information, which can be accessed securely as environment variables in your containers.

AWS Lambda takes care of most infrastructure security, but you are still responsible for setting up security properly. Each Lambda function can have specific security settings using IAM roles, allowing only authorized users to access them. Plus, every function runs in its own isolated environment, adding an extra security layer.

10. Setup and Maintenance

When comparing AWS Fargate vs Lambda for setup and maintenance, AWS Fargate requires you to package your app in containers and configure details like CPU, RAM, networking, and access management. While AWS manages scaling and provisioning resources for the containers, you still have more control over the runtime environment than Lambda.

On the other hand, AWS Lambda and AWS Fargate differ in how they handle setup and maintenance. With AWS Lambda, you can concentrate solely on your application code and functions. AWS handles everything else, including scaling, hardware management, operating system updates, and provisioning resources like CPU and RAM. It’s a serverless solution, meaning you don’t have to worry about infrastructure.

11. Reliability and Availability

When comparing Fargate vs Lambda for high availability, Fargate also offers high availability by managing infrastructure across multiple availability zones. However, redundancy and failover options in Fargate may require more setup than Lambda, which handles it automatically.

Lambda guarantees high availability by automatically managing the infrastructure in different locations. This ensures your functions are always available with minimal downtime.

AWS Fargate vs. Lambda: Deciding When to Use Each

When comparing AWS Fargate vs Lambda, choosing the right service depends on your app’s needs; however, let’s look at when to choose each for your business.

Fargate is Ideal in the following situations:

• Containerized applications: Fargate runs containers without managing servers or clusters.
• Applications that need long-running processes: This is ideal for applications requiring persistent state or longer execution times, like APIs or backend services.
• Custom configurations: Fargate is a good choice if you use specific configurations or software inside containers without managing the underlying infrastructure.

Lambda is ideal in the following situations

• Event-driven applications: Lambda is perfect for apps that react to certain events, like when a file is uploaded to S3 or an API is called. It runs your code automatically when needed, without needing you to manage the infrastructure.
• Microservices architecture: Lambda is ideal for microservices, where each function handles a small, independent task. This lets you focus on different parts of an app without managing servers.
• Real-time data processing: Lambda is great for handling real-time data, like data from IoT devices or live analytics, because it can quickly change to handle more or less traffic as needed.

How Lambda and Fargate Can Work Together:

1. Fargate for Backend Services or Resource-Intensive Workloads:

After the event processing (done by Lambda), Fargatecan run resource-intensive workloads like API services, databases, or data processing tasks that require long execution times.
Example: After Lambda processes the uploaded file, Fargate can run a containerized application to store the processed data, serve API requests, or run heavy computations.

2. Event-Driven Task Handling by Lambda:

Lambda handles quick, event-driven tasks that don’t require a server or persistent infrastructure.
Example: File Upload to S3 – When a file is uploaded to S3, Lambda can trigger the necessary code to process the file, such as resizing an image or processing data.

Key Consideration When Choosing Between Lambda vs Fargate

If you are confused about lambda vs Fargate, here are four key things to help you decide which option is best for your project:

1. Type of Application

• Fargate works best for applications that run for a long time or are more complex, like web servers or data processing tasks.
• Lambda is ideal for short tasks that respond to events, such as when a file is uploaded or an API call is made.

2. Cost

• Fargate charges you for your containers’ CPU and memory, even if they’re not running.
• Lambdacharges based on how long your functions run, so it’s cheaper for short tasks with low resource needs.

3. Scalability

• Fargate scales by adding more containers to handle traffic.
• Lambda scales by adjusting the resources for each function based on demand.

4. Team Expertise

• Fargate requires more management and knowledge of container orchestration (like ECS or EKS).
• AWS fully manages Lambda, so your team can focus just on coding without worrying about infrastructure.

Fargate vs Lambda: Key Takeaways

Frequently Asked Questions (FAQs)

Is Fargate better than Lambda?

It depends on your needs. Fargate is ideal for running containerized applications where you need more control over resources. Lambda is best for event-driven, serverless applications that run only when triggered.

When to use Fargate instead of Lambda?

Use Fargate to run containerized apps with specific resources (CPU, memory) and control over the environment. Use Lambda for quick, event-driven tasks like handling API calls or file uploads.

How many VCPUs can you have in Fargate?

Fargate allows you to choose from 0.25 to 4 vCPUs per task, depending on your needs.

Does Fargate have cold starts?

Yes, Fargate can have cold starts, but they tend to be less noticeable than Lambda’s since Fargate runs containers that stay active longer.

Is Fargate more secure?

Fargate provides strong isolation between tasks, but security depends on how well you configure your containers. Lambda also isolates functions well and handles most security, so both can be secure if configured properly.

Is it possible to use Fargate without EKS?

Yes, Fargate can be used without EKS. It works with Amazon ECS (Elastic Container Service) or with EKS for Kubernetes.

Is Fargate fully managed?

Yes, Fargate is fully managed, meaning AWS handles the infrastructure, scaling, and provisioning. You just manage the containers and their configuration.