A social media company allows users to upload images to an application hosted in AWS. The images must be automatically resized for multiple device types. Traffic is unpredictable throughout the day. The company wants a highly available solution that maximizes scalability. What should a solutions architect implement?

The correct solution leverages Amazon S3 for cost-effective, highly available static website hosting and AWS Lambda for serverless, scalable image resizing. When an image is uploaded to S3, an S3 event notification can trigger a Lambda function. This function resizes the image into multiple formats and stores them back into S3, providing a highly scalable and cost-effective solution for unpredictable traffic. Hosting a static website in Amazon CloudFront (an edge caching service) is incorrect because CloudFront delivers content, it doesn't host the origin website itself. Using AWS Step Functions for simple image resizing is overkill, and storing images in Amazon RDS (a relational database) is inappropriate for binary objects like images, which are better suited for object storage like S3. Running a dynamic website on an EC2 instance with an image resizing process is less scalable and highly available than a serverless approach. It requires managing servers and scaling them manually or with Auto Scaling, which adds operational overhead. While an Amazon ECS cluster with SQS for resize jobs offers scalability, running an image-resizing program on a separate EC2 instance to process SQS jobs introduces unnecessary server management and lacks the inherent scalability and cost-effectiveness of a serverless Lambda function for this specific task.