Tag: technical how-to

Many government agencies, like the National Oceanic and Atmospheric Administration (NOAA), participate in the AWS Open Data Sponsorship Program. In this post, we discuss how to use NOAA datasets in the Registry of Open Data on AWS using Amazon Bedrock Knowledge Bases.

Many organizations validate their generative AI–based workloads on their emotional reaction to a foundation model’s output instead of real testing criteria. In this post, we show you how you can move away from vibe testing and effectively evaluate your Amazon Bedrock workloads for production.

As more and more healthcare companies use their data to remain competitive, protecting patient data is as critical than ever. With increasing adoption of AI/ML models in healthcare, making sure that these technologies comply with privacy regulations such as HIPAA and GDPR has become a top priority. Amazon Bedrock is a fully managed service that provides unified access to a diverse selection of high-performance foundation models from industry-leading AI companies. In this post, we walk you through the importance of healthcare data privacy and how to use Amazon Bedrock Guardrails to safeguard sensitive information in AI-driven healthcare solutions.

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. 

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.

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.

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.

Government agencies handle vast volumes of bureaucratic documents daily, ranging from tax forms to medical records. This document-heavy workflow, often reliant on manual processing, can result in delays, errors, and increased operational inefficiencies, causing frustration among both employees and stakeholders. This post explores how intelligent document processing (IDP) solutions from Amazon Web Services (AWS) can modernize bureaucratic workflows, improve efficiency, and enhance service delivery within government agencies.