A company built an image analysis application where users upload photos and select photo frames. Currently it uses a single Amazon EC2 instance and Amazon DynamoDB for metadata. User traffic varies significantly by time of day and the number of concurrent users will grow. The company must ensure the application can scale to meet demand. Which solution meets these requirements?

This solution effectively addresses scalability and varying traffic. AWS Lambda is a serverless compute service that automatically scales to handle fluctuating workloads for photo processing without managing servers. Amazon S3 is a highly durable and scalable object storage service, ideal for storing large numbers of photos. Retaining DynamoDB for metadata is appropriate as it's a fully managed, high-performance NoSQL database that scales well. Incorrect options: Storing photos directly in DynamoDB is inefficient and expensive, as DynamoDB is optimized for key-value data, not large binary objects. Kinesis Data Firehose is for streaming data delivery, not for processing individual photo uploads or storing photos and metadata in a scalable, accessible manner for an application. Increasing EC2 instances alone doesn't provide the same level of automatic scaling as Lambda, and EBS volumes are tied to specific instances, making them less suitable for highly scalable, decoupled storage of photos across multiple compute resources.