AWS Batch is a set of batch management capabilities that enables developers, scientists, and engineers to easily and efficiently run hundreds of thousands of batch computing jobs on AWS. AWS Batch dynamically provisions the optimal quantity and type of compute resources (e.g., CPU or memory optimized instances) based on the volume and specific resource requirements of the batch jobs submitted. With AWS Batch, there is no need to install and manage batch computing software or server clusters, allowing you to instead focus on analyzing results and solving problems. AWS Batch plans, schedules, and executes your batch computing workloads using Amazon EC2 and Spot Instances.

Batch computing is the execution of a series of programs (“jobs”) on one or more computers without manual intervention. Input parameters are pre-defined through scripts, command-line arguments, control files, or job control language. A given batch job may depend on the completion of preceding jobs, or on the availability of certain inputs, making the sequencing and scheduling of multiple jobs important, and incompatible with interactive processing.

• It can shift the time of job processing to periods when greater or less expensive capacity is available.
• It avoids idling compute resources with frequent manual intervention and supervision.
• It increases efficiency by driving higher utilization of compute resources.
• It enables the prioritization of jobs, aligning resource allocation with business objectives.

AWS Batch handles job execution and compute resource management, allowing you to focus on developing applications or analyzing results instead of setting up and managing infrastructure. If you are considering running or moving batch workloads to AWS, you should consider using AWS Batch.

AWS Batch is optimized for batch computing and applications that scale through the execution of multiple jobs in parallel. Deep learning, genomics analysis, financial risk models, Monte Carlo simulations, animation rendering, media transcoding, image processing, and engineering simulations are all excellent examples of batch computing applications.

AWS Batch supports any job that can executed as a Docker container. Jobs specify their memory requirements and number of vCPUs.

There is no additional charge for AWS Batch. You only pay for the AWS Resources (e.g. EC2 Instances) you create to store and run your batch jobs.

Yes, you can use Batch to specify the number and type of accelerators your jobs require as job definition input variables, alongside the current options of vCPU and memory. AWS Batch will scale up instances appropriate for your jobs based on the required accelerators and isolate the accelerators according to each job’s needs, so only the appropriate containers can access them.