Which service is designed to run batch jobs at any scale on AWS?

AWS Batch is specifically designed to efficiently run batch jobs at any scale in the AWS cloud. This service allows users to submit jobs to a managed environment where it automatically provisions the optimal quantity and type of compute resources based on the volume and resource requirements of the jobs submitted.

The key benefit of AWS Batch is its ability to handle different sizes of batch processing workloads without requiring the user to manage the underlying infrastructure. Users can define a job queue, specify dependencies, and monitor job progress from a centralized console, making it a streamlined solution for batch processing. This service is particularly well-suited for tasks that can be parallelized and scaled, such as large-scale data processing, rendering, or scientific simulations.

In contrast, other services like AWS Lambda are designed for serverless computing that runs in response to events, rather than for executing batch jobs. Amazon EC2 provides virtual servers but requires manual setup and scaling for batch workloads, meaning it does not offer the automation that AWS Batch does for running batch processes. AWS Fargate, while it enables running containerized applications without managing servers, is focused on container orchestration rather than dedicated batch job processing.

Therefore, the clear choice for a service specifically tailored to handle batch jobs in a scalable and managed way is AWS