Amazon CloudFront Functions vs Lambda@Edge: Choosing the Right Solution

Choosing between CloudFront Functions and Lambda@Edge? This guide compares performance, cost, and use cases to help you pick the best edge computing solution for your needs.

In this article, you will learn:

• What Are Amazon CloudFront Functions?
• How CloudFront Functions Work
• Key Features & Benefits
• Common Use Cases
• What Is AWS Lambda@Edge?
• How Lambda@Edge Works
• Key Features & Benefits
• Common Use Cases
• Pricing Breakdown: Amazon CloudFront Functions vs Lambda@Edge
• Key Takeaway
• Key Differences Between Amazon CloudFront Functions vs Lambda@Edge
• When to Use Lambda at Edge vs CloudFront Functions
• Use CloudFront Functions when:
• Use Lambda@Edge when:
• Simple Process to Choose:
• Conclusion

When optimizing content delivery from AWS to clients, businesses sometimes need to execute custom logic at the edge of Amazon CloudFront CDN – whether for request modifications, authentication, or performance enhancements. AWS provides two key solutions for this: Amazon CloudFront Functions and Lambda@Edge.

Both services enable developers to process requests closer to end users, reducing latency and improving efficiency. However, they differ in capabilities, use cases, pricing and execution environments.

CloudFront Functions are designed for lightweight, high-performance tasks, while Lambda@Edge supports more complex operations with deeper integration across AWS services.

So, which one should you use? The right choice depends on factors like processing complexity, execution time, and integration needs. Let’s break down their differences to help you decide. Read on!

What Are Amazon CloudFront Functions?

CloudFront Functions are a lightweight, highly scalable serverless compute option designed to execute millisecond-level JavaScript logic at CloudFront edge locations. They operate at ultra-low latency, enabling quick request and response modifications without additional infrastructure overhead.

How CloudFront Functions Work

These functions execute synchronously within CloudFront’s viewer request or viewer response phases, meaning they can modify HTTP requests before they reach the origin or adjust responses before they reach the user.

Unlike Lambda@Edge, CloudFront Functions cannot access the network, read request bodies, or interact with the filesystem. This makes them highly efficient for lightweight tasks but limits their ability to handle complex processing.

Key Features & Benefits

• Execution Speed – Runs in under 1 millisecond, ideal for high-performance applications.
• Massive Scalability – Can scale to 10 million+ requests per second.
• Lower Pricing – Costs significantly less than Lambda@Edge, making it cost-effective for simple tasks.
• Edge-Level Execution – Runs directly at CloudFront edge locations without added latency.
• Key-Value Store – Enables low-latency data storage for use cases like URL rewrites, A/B testing, and access control.
• Origin Manipulation – Dynamically modify origin selection for simple load balancing, failover, and geo-based routing.

Common Use Cases

CloudFront Functions are ideal for lightweight processing tasks that require minimal compute power, such as:

• Redirects, changes HTTP status and URL rewrites

CloudFront Functions can be used to redirect users to new URLs dynamically. Redirect for example non-www domains to www domains or vice versa and redirect paths to specific pages, such as /old-path to /new-path. Modify the HTTP status code (302 to 301) received from the origin before delivering it to the viewer.

• Security Header Enforcement Enhance security by adding or modifying HTTP headers in responses. For example, implement HTTP Strict Transport Security (HSTS) headers to enforce secure connections.

• Cookie-Based Personalization Tailor content delivery based on user-specific data stored in cookies, such as serving personalized recommendations or localized content.

• Geolocation-Based Access Control Restrict or allow access to content based on the viewer's geographic location, enhancing compliance with regional content licensing agreements.

• Origin-Based Routing Using Viewer Location Use CloudFront Functions to determine the viewer’s geographic location and dynamically route cache-miss requests to the nearest AWS Region running your application. This helps reduce latency and improve performance without relying on origin-side logic.

While CloudFront Functions are excellent for simple, ultra-fast request transformations, they have limitations—such as the inability to interact with external AWS services or perform complex computations. For more advanced edge processing, Lambda@Edge is a better fit.

What Is AWS Lambda@Edge?

AWS Lambda@Edge is a fully managed serverless computing service that extends AWS Lambda’s capabilities to CloudFront’s global edge network, allowing businesses to run more complex logic closer to users. Unlike CloudFront Functions, Lambda@Edge supports stateful processing and can be connected to other services in AWS, enabling deeper integrations with AWS services, external APIs, and databases.

How Lambda@Edge Works

Lambda@Edge can execute at four different CloudFront lifecycle events:

1. Viewer Request – Runs before CloudFront forwards the request to the origin.
2. Origin Request – Executes before the request reaches the backend server.
3. Origin Response – Processes responses before they are returned to CloudFront.
4. Viewer Response – Modifies responses before sending them to end users.

Because Lambda@Edge runs Node.js and Python, it allows for much more advanced logic, including API calls, authentication checks, and content personalization. Additionally, Lambda@Edge can access the network, read request bodies, and interact with the filesystem, making it suitable for tasks requiring external service interactions. However, it has slightly higher latency and cost compared to CloudFront Functions.

Key Features & Benefits

• Broader Language Support – Works with Node.js and Python, allowing more complex scripting.
• Stateful and API-Driven – Can interact with AWS services (S3, DynamoDB, API Gateway) and third-party APIs.
• Flexible Execution Points – Runs at viewer request, origin request, origin response, and viewer response stages.
• Custom Security & Authentication – Can validate JWT tokens, enforce authentication rules, and control access based on user identity.
• Otherwise, it can do the same things as CloudFront functions described before.

Common Use Cases

Lambda@Edge is ideal for scenarios that require deeper logic and AWS service integration, such as:

• User authentication – Validate user tokens, implement SSO, or apply custom authorization.
• Personalized content delivery – Serve tailored experiences based on geolocation, cookies, or user preferences.
• Advanced logging & analytics – Capture request metadata, generate real-time logs, and store them in S3 or DynamoDB.
• Dynamic content transformation – Modify responses on the fly, such as compressing images or rewriting API responses.
• A/B testing for frontend applications – Dynamically split traffic for testing different UI versions without backend changes.
• Server-side rendering (SSR) for SPAs – Render dynamic content closer to users, improving page load speed and performance.
• Real-time API request validation – Authenticate API requests or enforce security checks before requests reach backend services.

Because Lambda@Edge can make external calls and perform computational tasks, it is the preferred choice for stateful, API-driven, or security-focused applications.

For a deeper breakdown of how Lambda@Edge works, check out our detailed guide: Lambda@Edge Explained.

Pricing Breakdown: Amazon CloudFront Functions vs Lambda@Edge

Amazon CloudFront Functions follow a flat-rate pricing model of $0.10 per 1 million invocations, regardless of execution time. Since they run within 1 millisecond, there are no additional compute costs, making them a cost-effective option for simple request modifications.

AWS Lambda@Edge pricing is based on two factors:

1. Number of requests – Costs $0.60 per 1 million requests ($0.0000006 per request). Pricing remains consistent across AWS regions.
2. Function duration – Costs $0.00005001 per GB-second used. For example, a function with 128MB of memory incurs a duration charge of $0.00000625125 per 128MB-second used. Lambda@Edge is metered in 50ms increments.

Key Takeaway

• CloudFront Functions are cheaper and best for lightweight processing.
• Lambda@Edge incurs higher costs due to compute time, memory usage, and data transfer fees, but provides more flexibility for complex workloads.

Key Differences Between Amazon CloudFront Functions vs Lambda@Edge

When to Use Lambda at Edge vs CloudFront Functions

Choosing between CloudFront Functions and Lambda@Edge depends on the complexity of your processing needs, latency requirements, and budget constraints. While both services execute logic at AWS edge locations, they cater to different use cases.

Use CloudFront Functions when:

• You need millisecond-level execution speed for ultra-low latency tasks.
• The function only modifies headers, URLs, or request properties before reaching the origin.
• You require cost-efficient and scalable execution for lightweight workloads.
• The logic does not require interaction with AWS services or external APIs.

Use Lambda@Edge when:

• You need to call external services like S3, DynamoDB, or third-party APIs.
• The function requires complex logic, such as authentication, data processing, or real-time content transformation.
• You need access to multiple execution points (viewer request, origin request, origin response, viewer response).
• The workload involves personalized content delivery or advanced security handling.

Simple Process to Choose:

If you think you need Lambda@Edge, always check if it's possible to achieve the same result with CloudFront Functions.

1. Check the task complexity: Simple tasks (e.g., modify headers, URLs, or request properties): CloudFront Functions. Complex tasks (e.g., call external services, complex logic, real-time processing): Lambda@Edge.
2. Consider performance needs: Ultra-low latency: CloudFront Functions (faster, lower cost). More processing power needed: Lambda@Edge (more flexible, higher cost).
3. Budget and scalability: Lightweight tasks: CloudFront Functions (cheaper and scalable). Heavy tasks: Lambda@Edge (more capabilities but higher cost).

Having trouble making a decision? At Stormit, we have CloudFront Service Delivery expertise, and our team of certified AWS Solutions Architects can help you choose the best solution for a well-architected infrastructure.

Contact Us

Conclusion

Both CloudFront Functions and Lambda@Edge serve unique purposes in edge computing. CloudFront Functions are best for fast, cost-effective request transformations, while Lambda@Edge is ideal for stateful, API-driven, and compute-heavy processing. Choosing the right solution depends on your workload’s complexity, latency requirements, and budget.

For workloads requiring simple request modifications with minimal compute overhead, CloudFront Functions provide an efficient, scalable, and cost-effective solution. Meanwhile, applications that demand deeper integrations with AWS services, personalized content, or network access benefit from the flexibility of Lambda@Edge.

By carefully assessing your business needs and evaluating workload requirements, you can optimize costs while maintaining performance and scalability.

As you continue to develop and optimize your cloud strategy, follow Stormit’s blog for more valuable content on cloud technologies and best practices.