AWS Lambda vs. Fargate: Which is Right for Your Containers?

Running containers on AWS has never been easier, but choosing the right compute service can be tricky. The two leading serverless options for containers are AWS Lambda and AWS Fargate.

While both services allow you to run containers without managing underlying EC2 instances, they are designed for fundamentally different use cases.

AWS Lambda for Containers

Since 2020, AWS Lambda has supported running container images (up to 10 GB in size) as functions. You package your application code and dependencies into a container image, and Lambda runs it just like a standard .zip-based function.

How it Works:

• You define a container image with a specific entry point that conforms to the Lambda Runtime API.
• When an event triggers your function, Lambda provisions an environment, runs your container, and executes the code.
• The execution is time-limited (max 15 minutes).

Strengths:

• Event-Driven and Scalable: Scales from zero to thousands of instances in seconds in response to events. You never pay for idle.
• Simplicity: Integrates seamlessly with over 200 AWS services as event sources (API Gateway, S3, SQS, etc.).
• Pay-per-Millisecond: You are billed only for the execution time of your code, making it extremely cost-effective for intermittent or variable traffic.

Weaknesses:

• Short-Lived Executions: The 15-minute maximum execution time makes it unsuitable for long-running processes.
• Limited Resources: Maximum memory is 10 GB and CPU is allocated proportionally. Not suitable for heavy compute tasks.
• Cold Starts: There can be a startup latency (cold start) when a new environment is provisioned, which can be a concern for latency-sensitive applications.

Best For: Short-lived, event-driven tasks; APIs with variable traffic; data processing jobs.

AWS Fargate: Serverless Compute for Containers

AWS Fargate is a serverless compute engine for containers that works with both Amazon Elastic Container Service (ECS) and Amazon Elastic Kubernetes Service (EKS). You define your application as a "task" with specific CPU and memory requirements, and Fargate runs it for you.

How it Works:

• You package your application in a container image.
• You define an ECS Task Definition or Kubernetes Pod, specifying the container image, CPU, memory, and networking.
• You run the task as part of a long-running service (e.g., behind a load balancer) or as a standalone scheduled task.

Strengths:

• Long-Running Processes: Fargate tasks can run continuously, 24/7. This makes it perfect for traditional web servers, backend services, or any persistent application.
• More Resources: You can provision much larger tasks (up to 16 vCPU and 120 GB of memory), making it suitable for more demanding compute and memory-intensive workloads.
• No Cold Starts (for Services): For a long-running service, the container is always warm and ready to accept requests, eliminating cold start latency.
• Full Container Control: You have more control over the networking, storage, and runtime environment compared to Lambda.

Weaknesses:

• Cost Model: You pay for the CPU and memory you provision for the entire time your task is running, whether it's processing requests or sitting idle. This can be less cost-effective for spiky or infrequent workloads.
• Slower Scaling: Scaling up by launching new Fargate tasks takes longer (typically a minute or two) than Lambda's sub-second scaling.

Comparison at a Glance

Feature	AWS Lambda for Containers	AWS Fargate
Execution Model	Short-lived, event-triggered (max 15 min)	Long-running services or tasks
Billing Model	Pay-per-millisecond of execution	Pay for provisioned vCPU & memory per second
Scaling	Near-instant, scales to zero	Slower (minutes), scales to a minimum of 1
Primary Use Case	APIs, event processing, cron jobs	Web servers, backend APIs, persistent services
Resource Limits	Max 10 GB Memory	Max 120 GB Memory, 16 vCPU

Conclusion: Which Should You Choose?

The decision comes down to your application's execution pattern.

• Choose AWS Lambda if your workload is:

  • Event-driven: Triggered by S3 events, SQS messages, or API Gateway requests.
  • Short-lived: Completes its task in under 15 minutes.
  • Has variable or unpredictable traffic: The scale-to-zero capability will save you a lot of money.

• Choose AWS Fargate if your workload is:

  • A long-running service: Like a traditional web server or a persistent backend API that needs to be always on.
  • Requires more CPU or memory than Lambda can provide.
  • Cannot tolerate cold start latency for any request.

Often, the best architecture involves using both. You might have a core API running as a persistent service on Fargate, which then offloads asynchronous, event-driven tasks (like sending emails or processing images) to Lambda functions.