A company is building a shopping application on AWS. The catalog changes once per month and must scale with traffic. The company wants the lowest possible latency. Each user's shopping cart data must be highly available and must persist if the user disconnects and later reconnects. What should a solutions architect do to ensure shopping cart data is preserved at all times?

The correct option is to configure Amazon ElastiCache for Redis. Redis is an in-memory data store that provides extremely low latency, making it ideal for caching frequently accessed catalog data and storing volatile session data like shopping carts. Its high availability features ensure data persistence even if a user disconnects. Incorrect options: Application Load Balancer sticky sessions are for directing a user's requests to the same backend instance, not for persisting shopping cart data across disconnections or for caching. Aurora is a relational database, not optimized for low-latency caching or session state. Amazon OpenSearch Service is a search and analytics engine, not designed for low-latency caching of general data or for storing user session data like shopping carts. Using an Amazon EC2 instance with EBS for catalog and shopping cart data would be much slower and less scalable than ElastiCache for Redis, and managing persistence and high availability for session data would be complex.