AWS Open Source Blog

Category: Amazon EC2

Continuous delivery with server-side Swift on Amazon Linux 2

In January, I published an article describing how to use AWS tools to build, test, and release server-side Swift code on two platforms: Amazon Elastic Container Service (Amazon ECS) and Elastic Compute Cloud (Amazon EC2) running Ubuntu Linux. Recently Swift.org has released official support for the Amazon Linux 2 operating system. This article is a […]

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Deploy, track, and roll back RDS database code changes using open source tools Liquibase and Jenkins

Customers across industries and verticals deal with relational database code deployment. In most cases, developers rely on database administrators (DBAs) to perform the database code deployment. This works well when the number of databases and the amount of database code changes are low. As organizations scale, however, they deal with different database engines—including Oracle, SQL […]

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AutoGluon how-to tutorial

Machine learning with AutoGluon, an open source AutoML library

If you work in data science, you might think that the hardest thing about machine learning is not knowing when you’ll be done. You start with a problem, a dataset, and an idea about how to solve it, but you never know whether your approach is going to work until later, after you’ve wasted time. […]

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laptop on a desk

Getting started with Jitsi, an open source web conferencing solution

Teams across the world are looking for solutions that help them to work and collaborate online in these unprecedented times. There are many options that customers have, so this post will help provide you with some options if you are looking. Many teams choose to use managed solutions to enable collaboration. If your business needs […]

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diagram of host machine, container, code, and datasets and checkpoints

Why use Docker containers for machine learning development?

I like prototyping on my laptop, as much as the next person. When I want to collaborate, I push my code to GitHub and invite collaborators. And when I want to run experiments and need more compute power, I rent CPU and GPU instances in the cloud, copy my code and dependencies over, and run […]

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User uploads data in BIDS format to S3 and starts the Lambda function → Lambda parses the uploaded data and launches a cluster of EC2 instances → EC2 instances run fMRIprep which preprocesses the data → preprocessed data are saved to S3.

fMRI data preprocessing on AWS using fMRIprep

A typical fMRI study often produces imaging data of terabytes or more. Storing and preprocessing this data can be challenging on a single computer because it often has neither enough disk space to store the data nor enough computing power to preprocess it. Traditionally, researchers use a combination of cloud-based storage and on-premises high-performance clusters […]

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VMD over NICE DCV.

Deploying an HPC cluster and remote visualization in a single step using AWS ParallelCluster

Since its initial release in November 2018, AWS ParallelCluster (an AWS-supported open source tool) has made it easier and more cost effective for users to manage and deploy HPC clusters in the cloud. Since then, the team has continued to enhance the product with more configuration flexibility and enhancements like built-in support for the Elastic […]

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AWS Fargate container logs collection and analysis with AWS FireLens and Sumo Logic

AWS Fargate is a compute engine for Amazon ECS that allows you to run containers without having to manage servers or clusters. Fargate manages provisioning, configuration, and scaling of the clusters. With Fargate, you can focus on your application design and implementation instead of worrying about the infrastructure. In this post, we’ll provide an overview […]

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Best Practices for Running Ansys Fluent Using AWS ParallelCluster

Using HPC (high performance computing) to solve Computational Fluid Dynamics (CFD) challenges has become common practice. As the growth from HPC workstation to supercomputer has slowed over the last decade or two, compute clusters have increasingly taken the place of single, big SMP (shared memory processing) supercomputers, and have become the ‘new normal’. Another, more […]

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