Batch processing for ML model training, simulation, and analysis at any scale

Fully managed batch processing

AWS Batch is a fully managed batch computing service that plans, schedules, and runs your containerized batch ML, simulation, and analytics workloads across the full range of AWS compute offerings, such as Amazon ECS, Amazon EKS, AWS Fargate, and Spot or On-Demand Instances.

Benefits of AWS Batch

Focus on analyzing results, not managing infrastructure

Run hundreds of thousands of batch machine learning (ML), simulation, and analytics computing jobs without installing software or servers.

Native integration with AWS

Natively integrate with AWS to implement scaling, networking, and management capabilities.

Optimize compute costs

Reduce costs by optimizing computing job distribution based on volume and resource requirements.

Scale compute resources automatically

Scale your compute resources automatically with fully managed infrastructure that supports large-scale processing and simulations.

Use cases

Test complex systems using simulation

Run simulations at scale when testing complex systems like those used in robotics, autonomous vehicles, and advanced driver assistance systems (ADAS).

Run financial services analyses

Automate analyses of the day’s transaction costs, completion reports, and market performance.

Screen for drugs and sequence genomes

Rapidly search libraries of small molecules to capture better data for drug design.

Render visual effects

Automate content-rendering workloads and reduce the need for human intervention due to dependencies.

Train ML models

Efficiently run compute-intense ML model training and inference at any scale.