Category: AWS Identity and Access Management (IAM)

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.

Organizations require solutions for real time or near real time dashboards that can be provided to their customers without impacting their database performance or service level agreements (SLAs) to their end users. In this post, we showcase the integration of Amazon Web Services (AWS) capabilities to present an end-to-end architecture for this data flow.

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.

To remain viable and continue to fulfill their mission, educational institutions are constantly seeking ways to optimize their IT costs while maintaining high-quality services. One often overlooked area for potential savings is the management of cloud resources, particularly Amazon Elastic Compute Cloud (Amazon EC2) instances. Many universities and colleges find themselves facing unexpected costs when EC2 instances are left running during off-peak hours or periods of inactivity. In this post, we explore how higher education customers can implement automatic shutdown mechanisms for EC2 instances, significantly reducing cloud expenses.

In an earlier post, Build secure and scalable data platforms for the European Health Data Space (EHDS) with AWS, we discussed a reference architecture for building secure and scalable data platforms for secondary usage of health data in alignment with the European Health Data Space (EHDS) using Amazon Web Services (AWS). This follow-up post walks you through the technical implementation details for building such federated data governance and analysis platforms using AWS. Whether you are a healthcare organization, technology provider, or systems integrator, this post aims to equip you with the technical knowledge to build a secure data platform for secondary usage of health data in alignment with the EHDS Regulation.

The healthcare industry is undergoing a profound transformation, driven by the adoption of generative artificial intelligence (AI), cloud computing, and connected care devices. This digital revolution promises to improve patient outcomes, reduce costs, and enhance the overall healthcare experience. However, it also introduces new challenges in terms of cybersecurity, privacy, and regulatory compliance. To navigate this complex landscape, healthcare organizations are turning to scalable, affordable, and highly available cloud infrastructures such as Amazon Web Services (AWS) to build resilient, secure, and innovative solutions.

AWS App Studio is a low-code development platform for users to build, deploy, and manage applications without extensive coding knowledge. It is designed to streamline the application development process, making it more accessible to a wider range of users, including business users, IT professionals, and startups that don’t have large specialized IT teams. This post guides you through the process of creating a user-friendly create, read, update, and delete (CRUD) application to efficiently manage birth certificate applications using AWS App Studio.

Today, generative artificial intelligence (AI) is at the core of many of the decisions and technologies businesses across the globe are implementing. The linchpin to ensuring that generative AI is effective depends on the foundation models (FMs) storing the data. To make sure that those FMs are pulling the correct data, Amazon Web Services (AWS) has developed a solution through Amazon Bedrock to generate SQL to answer user questions about the data. The solution was developed to support the Federal Institute of São Paulo (IFSP) and has optimized their decision-making.

In this post, we explore how AWS services, open source software, and bespoke source code can help address resource sharing enhancements requested by public sector customers using AWS Outposts. This solution aims to provide greater flexibility, control, and cost management for organizations leveraging Outposts in multi-account environments, specifically focusing on key AWS resources, including Amazon Elastic Compute Cloud (Amazon EC2), Amazon Elastic Block Store (Amazon EBS), and Amazon Simple Storage Service (Amazon S3) on Outposts.

PubMed Central (PMC) is a leading resource for biomedical literature, offering a vast repository of full-text biomedical and life sciences journal articles. While PMC offers immense potential to accelerate scientific progress, inform evidence-based practice, and drive innovation in the biomedical and life sciences fields, the sheer volume of data presents a significant challenge. This is where Amazon Q Business comes in. It’s a powerful service designed to streamline the process of analyzing vast amounts of scientific literature and provide valuable insights efficiently. Read this post to learn more.