The core issue is high latency when serving images during traffic spikes. The current design resizes images dynamically and caches them locally inside ECS containers. With AWS Fargate, containers are ephemeral and scale in and out based on load. Local container caches are not shared across tasks, so cache hit rates drop during scaling events, forcing repeated image resizing. This increases CPU usage, startup latency, and response times under load.
The lowest operational overhead and most effective solution is to offload image delivery entirely from the application layer and use edge caching. Amazon CloudFront is designed to cache static content at edge locations close to end users, dramatically reducing latency and backend load. Amazon S3 is a durable, highly scalable object store that is well suited for serving static assets such as images.
Option A moves image delivery to a CloudFront + S3 architecture. By pre-scaling images and storing them in S3, the application no longer performs on-demand image resizing during requests. CloudFront caches the images at edge locations, so subsequent requests are served directly from the edge with minimal latency. The ALB remains the origin for dynamic content, while image requests are routed to the S3 origin using cache behaviors. This approach is fully managed, highly scalable, and requires minimal changes to the application logic once images are pre-generated.
Option B introduces ElastiCache, which adds operational overhead and complexity. The application must manage cache keys, eviction, and failure scenarios. ElastiCache is better suited for low-latency data access patterns rather than large static objects like images, and it does not provide global edge caching.
Option C adds unnecessary complexity by introducing an Aurora database as part of the caching layer. Databases are not designed to manage cache metadata for static assets at scale, and this design increases operational overhead without improving latency compared to CloudFront.
Option D is not appropriate because API Gateway caching is intended for API responses, not for efficient delivery of large static binary objects such as images. Replacing the ALB with API Gateway also introduces request size, payload, and cost considerations and does not provide global edge caching comparable to CloudFront for image delivery.
Therefore, using Amazon CloudFront with Amazon S3 for pre-scaled images provides the lowest latency, highest scalability, and least operational overhead.
[References:AWS documentation on Amazon CloudFront for low-latency delivery of static content through global edge caching.AWS documentation on Amazon S3 as a scalable origin for static assets and integration with CloudFront.AWS best practices for separating static content delivery from dynamic application workloads to reduce backend load and improve performance., , , ]
