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The ability to dynamically scale resources in response to demand is primarily associated with Amazon EC2 Auto Scaling. This service allows users to automatically adjust the number of EC2 instances running in response to the current workload, ensuring that there are enough resources available during peak times and that resources can be reduced during lower demand to save costs.

EC2 Auto Scaling continuously monitors the application's performance and can trigger scaling actions based on pre-defined conditions such as CPU utilization or request counts, thus providing a highly elastic environment. This dynamic scaling capability helps to maintain application performance and availability while optimizing costs effectively.

In contrast, while other options like AWS Lambda do offer scaling capabilities, they do so based on a different model. Lambda automatically scales to the number of requests received without requiring users to manage the underlying server instances. Amazon RDS offers scaling capabilities, particularly via its read replicas and scaling up or down for database instances, but it is not focused on automatic scaling of resources across a fleet as EC2 Auto Scaling is. Lastly, Amazon S3 is a storage service that handles large amounts of data and is built to scale automatically, but it does not involve scaling in terms of compute resources. Therefore, Amazon EC2 Auto Scaling is the correct choice for dynamically scaling resources based on demand