Pay-as-you-go resources are a compelling but budget-limited researchers performing HPC workloads need help working within the bounds of their grants. In this post, we show how to build a real-time cost guardian for AWS Batch to help enforce …
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Amazon SageMaker is a fully-managed service that provides every developer and data scientist with the ability to quickly build, train, and deploy machine learning (ML) models at scale. ML is realized in inference. SageMaker offers four …
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Since it was launched in 2017, AWS Batch has used the Amazon Elastic Container Service (Amazon ECS) to create the clusters it uses for deploying container jobs. That included AWS Fargate, which is a serverless face to ECS. But starting …
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Today I’m pleased to announce AWS Batch for Amazon Elastic Kubernetes Service (EKS). AWS Batch for Amazon EKS is ideal for customers who no longer want to shoulder the burden of configuring, fine-tuning, and managing Kubernetes clusters and …
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Today, we discuss AWS batch on Amazon EKS, and the initial motivation and design choices the team made when we developed the service, and some of the challenges to overcome. Read the Post on the AWS Blog Channel
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Today we are excited to announce that all 9000+ applications provided by the BioContainers community are available within ECR Public Gallery! You don’t need an AWS account to access these images, but having one allows many more pulls to the …
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In this post, we describe how to orchestrate protein folding jobs on AWS Batch. We also compare the performance of OpenFold and AlphaFold on a set of public targets. Finally, we will discuss how to optimize your protein folding costs. Read …
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AWS service teams continuously improve the underlying infrastructure and operations of managed services, and AWS Batch is no exception. The AWS Batch team recently moved most of their job scheduler fleet to a serverless infrastructure model …
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