Tag: Amazon S3

Fair Trade USA™ is a nonprofit organization that is committed to eliminating poverty by promoting sustainable development through ethical trade. They work to ensure fair compensation, safe working conditions for farmers and workers, and sustainable farming practices. In this post, you’ll learn how Fair Trade USA leverages Amazon Web Services (AWS) to improve working conditions for farmers and producers around the world.

In this post, we explore how AWS enables the automation of deploying a DPI-based solution stack. We highlight Sunbird RC (Registry and Credentials) as a real-world digital public goods (DPG) building block. The following example provides an overview and execution of the packaging available in the Sunbird community GitHub repository for provisioning required AWS services and deploying Sunbird RC services.

In recent years, public sector organizations have found success running their scientific data processing workloads on Amazon Web Services. As the number of workloads increase with the massive data volume and complex scientific simulations, organizations are looking for ways to optimize cost while maintaining research momentum. Amazon EC2 Spot Instances presents a compelling option to run unused Amazon Elastic Compute Cloud (Amazon EC2) capacity with an up to 90 percent discount compared to On-Demand prices. However, the intermittent nature of Spot Instances often requires careful consideration, especially when handling time-sensitive mission-critical workloads. In this post, we discuss how organizations can effectively identify opportunities to use Spot Instances and Amazon Q Business to develop an enhanced Spot Instance analysis. 

Academic research IT departments around the world face the same challenge: how to balance their existing on-premises infrastructure with the opportunities of cloud computing. At the Supercomputing 2024 (SC24) conference, Amazon Web Services hosted a panel featuring two research IT leaders: Circe Tsui, associate director of solutions architecture at Emory University in the Office of Information Technology, and Dr. Robert Shen, director of the RMIT AWS Supercomputing Hub (RACE) at the Royal Melbourne Institute of Technology (RMIT). During the panel, Tsui and Shen shared how their institutions use AWS to augment and enhance their research operations with more scalability, security, and collaboration alongside their on-premises infrastructure. Read this post to learn more.

Some customers using Amazon Web Services (AWS) prohibit users from installing software from public sources. Recently, the Landing Zone Accelerator on AWS (LZA) solution added optional capabilities to support this use case. Instead of installing directly from the public LZA GitHub repository, which is the default installation path for most customers, LZA can be self-hosted from your own Amazon Simple Storage Service (Amazon S3) bucket. This post shows the technical steps necessary to install LZA using Amazon S3.

As the primary agency of the US government responsible for biomedical and public health research, the National Institutes of Health (NIH) is one of the leading medical research centers in the world. The NIH Office of Portfolio Analysis (OPA) is tasked with helping NIH prioritize its research. OPA wanted to find a better way to optimize its cloud costs as its analytical research demands continued to grow. That need led OPA to work with AWS Partner Govplace, a systems integrator and solution provider for the public sector. Read this post to learn more about how OPA reduced research costs and scaled on demand.

Amazon Web Services (AWS) customers building software-defined ground segment solutions with the AWS Ground Station now have more confidence in their solution: they can integrate their DevOps practices with AWS Ground Station’s digital twin feature, which became generally available in August. The digital twin is useful for both aspiring and existing AWS Ground Station customers to achieve faster outcomes without applying for satellite licensing and more cost-effectively than scheduling a production satellite contact. Read this post to learn more.

This post explores the architectural design and security concepts employed by Radboud University Medical Center Nijmegen (Radboudumc) to build a secure artificial intelligence (AI) runtime environment on Amazon Web Services (AWS). Business leaders dealing with sensitive or regulated data will find this post invaluable because it demonstrates a proven approach to using the power of AI while maintaining strict data privacy and security standards.

In the age of generative artificial intelligence (AI), data isn’t just king—it’s the entire kingdom. Our previous blog post, Anduril unleashes the power of RAG with enterprise search chatbot Alfred on AWS, highlighted how Anduril Industries revolutionized enterprise search with Alfred, their innovative chat-based assistant powered by Retrieval-Augmented Generation (RAG) architecture. In this post, we examine the technical intricacies that make this system possible.

Data Review & Transfer Component (DRTC) on Amazon Web Services (AWS) provides a seamless solution to review, approve, and automate sensitive data transfer requests into and out of secure enclaves. In this post, we take you through the benefits of using DRTC to review data and other research artifacts for sensitivity prior to transfer into and out of these secure environments, in particular Trusted Research Environments (TREs).