AWS Batch is designed to facilitate which of the following?

AWS Batch is specifically designed to run batch computing workloads efficiently. This service enables users to define and submit batch jobs without managing the underlying infrastructure. With AWS Batch, you can easily scale the execution of jobs up or down based on the volume of tasks and requirements, automatically provisioning the optimal quantity and type of compute resources, such as CPUs and memory. This allows organizations to process large datasets or perform complex calculations in discrete jobs rather than in real-time streams.

The focus of AWS Batch is on executing batch workloads, which can be characterized as jobs that are processed in bulk rather than individually in real-time. This is particularly useful for scenarios like data processing, rendering, or any scenario where tasks can be queued and executed as resources become available.

The other options, while they represent valuable services in the AWS ecosystem, do not align with the primary function of AWS Batch. For instance, container management pertains more to services like Amazon ECS or EKS, while real-time data processing is generally associated with services such as AWS Lambda or Amazon Kinesis. Similarly, web application hosting is primarily handled by services like Amazon EC2 or AWS Elastic Beanstalk. Thus, the distinct focus on batch workloads clearly identifies option C as the correct response.