Category: AWS Batch

Last year, we published the Genomics Secondary Analysis Using AWS Step Functions and AWS Batch solution as a companion solution to the Genomics Data Transfer, Analytics, and Machine Learning Using AWS Services whitepaper. Since then, many customers have used the secondary analysis solution to automate their bioinformatics pipelines in AWS. A common pain point expressed […]

AWS Batch is a service that enables scientists and engineers to run computational workloads at virtually any scale without requiring them to manage a complex architecture. In this blog post, we share a set of best practices and practical guidance devised from our experience working with customers in running and optimizing their computational workloads. The readers will learn how to optimize their costs with Amazon EC2 Spot on AWS Batch, how to troubleshoot their architecture should an issue arise and how to tune their architecture and containers layout to run at scale.

Batch processing is a common need across varied machine learning use cases such as video production, financial modeling, drug discovery, or genomic research. The elasticity of the cloud provides efficient ways to scale and simplify batch processing workloads while cutting costs. In this post, you’ll learn a scalable and cost-effective approach to configure AWS Batch Array jobs to process datasets that are stored on Amazon S3 and presented to compute instances with Amazon FSx for Lustre.

A customer asked us what is the difference between the CancelJob and TerminateJob API calls in AWS Batch. This post provides an overview of AWS Batch job states, and how these two API calls effect the job requests that you have submitted.

Large-scale data analysis usually involves some multi-step process where the output of one job acts as the input of subsequent jobs. Customers using AWS Batch for data analysis want a simple and performant storage solution to share with and between jobs. We are excited to announce that customers can now use Amazon Elastic File System (Amazon […]

This post is written by Deepak Singh, Vice President of Compute Services. At AWS, we love working with customers to solve their toughest challenges. High performance computing (HPC) is one of those challenges that pushes against the boundaries of AWS performance at scale. HPC is also a personal interest of mine, as I came to […]