A company is creating a new web application for its subscribers. The application will consist of a static single page and a persistent database layer. Traffic peaks at millions of users for 4 hours each morning, and drops to only a few thousand users for the rest of the day. The company's data architects require the ability to rapidly evolve their schema. Which solutions will meet these requirements and provide the MOST scalability? (Choose two.)

The correct options provide a highly scalable and cost-effective solution for the described workload. Deploying static content to Amazon S3 and distributing it via Amazon CloudFront is the standard, most scalable, and cost-effective approach for static web content, handling millions of users efficiently. Amazon DynamoDB with on-demand capacity is an excellent choice for a database that needs to scale rapidly and handle unpredictable traffic patterns, like the described peak usage. Its schemaless nature also supports rapid schema evolution. Incorrect options: Amazon Aurora Serverless is a good option for variable workloads but might not match DynamoDB's extreme scalability and cost-effectiveness for this specific access pattern and schema flexibility requirement. While DynamoDB auto scaling is generally good, on-demand capacity is even better for highly spiky, unpredictable workloads as it instantly adapts without needing to configure scaling policies. Deploying EC2 instances for static content is overkill and less scalable and cost-effective than S3/CloudFront. EFS is also not designed for serving static web content directly to end-users at scale.