What you need to know about AWS Batch on Fargate

Brendan Bouffler
Date : January 18, 2024
Categories : AI/ML ,AWS Batch ,AWS ParallelCluster ,Amazon NICE DCV ,Elastic Fabric Adapter ,Life Sciences
Tags : ai ml ,aws ,batch ,cpus ,dcv ,ec2 ,efa ,gpus ,hpc ,high performance computing ,lustre ,mpi ,nccl ,parallel cluster ,schedulers ,storage ,autoscaling ,aws batch ,batch ,bioinformatics ,cloud computing ,elastic ,elastic fabric adapter ,fargate ,hpc instances ,infiniband ,job scheduling ,scientific computing ,supercomputing ,technical computing ,tightly coupled ,virtualization ,vizualization ,techshorts

Fargate is almost like having a magical compute engine. You simply provide the container image and Fargate launches it for you in seconds. No servers to manage, no infrastructure to configure. Fargate auto-scales and load balances your containers and handles infrastructure security for you.

With AWS Batch on Fargate, you get all the power and automation of AWS Batch for scheduling and running batch jobs, combined with the speed, scalability, and ease-of-use of Fargate. No longer do you need to manage EC2 instances yourself.

The benefits are clear:

Faster start times to spin up compute
Auto-scaling of resources to match workload
Pay-per-use pricing - no idle capacity
Built-in security and infrastructure management

Whether you’re new to batch processing or an expert, Fargate can make your workloads easier. See for yourself and try AWS Batch on Fargate today!

Angel Pizarro, our awesome Principal Developer Advocate for Batch swung by the Tech Shorts channel to help us understand how it all works.

If you have ideas for technical topics you’d like to see us cover in a future show, let us know by emailing us at ask-hpc@amazon.com.