Lambda@Edge for speeding up weather forecast for global users

[Awsbroz]

Query – One of the wrong choices has following explanation – This is a good solution for caching, however, this solution will not be able to serve the expected peak traffic during weather events. Lambda@Edge can serve only up to 10,000 requests per second.

My question is: How is it a good solution for caching as Lambda functions are mainly used for compute. And second, what are we computing on the Edge ? I believe both the choices mentioning Lambda@Edge are far stretched and explanation should have been that we dont need Lambda@Edge for caching rather than mentioning their limitations on concurrency and throughput ?

Please let me know if I am missing something.

Following is the question –

Category: CSAP – Continuous Improvement for Existing Solutions
A company wants to release a weather forecasting app for mobile users. The application servers generate a weather forecast every 15 minutes, and each forecast update overwrites the older forecast data. Each weather forecast outputs approximately 1 billion unique data points, where each point is about 20 bytes in size. This results in about 20GB of data for each forecast. Approximately 1,500 global users access the forecast data concurrently every second, and this traffic can spike up to 10 times more during weather events. The company wants users to have a good experience when using the weather forecast application so it requires that each user query must be processed in less than two seconds.

[Neil-TutorialsDojo]

Hello Awsbroz,

Good day!

Thank you for your question and feedback.

The explanation aims to clarify that while Lambda@Edge isn’t primarily for caching large datasets, it can enhance content delivery by executing logic at edge locations. However, you are correct that Lambda@Edge is mainly designed for computing, and the actual caching happens in Amazon CloudFront. What Lambda@Edge does is allow custom behavior—such as modifying requests or responses or implementing specific logic—closer to the user. In this context, the explanation focused on its limitations in handling traffic rather than pointing out that caching itself is handled by CloudFront.

We agree that the emphasis on not needing Lambda@Edge for caching in this specific scenario could have been more precise. The explanation will be updated to reflect that distinction better and avoid confusion between computing functions and actual caching mechanisms.

We appreciate your keen observation and will make adjustments to improve clarity going forward!

Regards,

Neil @ Tutorials Dojo