Tag: technical how-to

Healthcare providers and healthcare systems want to modernize their healthcare data exchanges so they can better analyze and gain more insight from their clinical data. In this walkthrough, learn how to use AWS to migrate legacy healthcare messaging data into Amazon HealthLake, which can use artificial intelligence (AI) and machine learning (ML) to discover meaningful and actionable healthcare information embedded in unstructured text.

Learn how government agencies can use AWS to build data interchange zones to automate their ability to ingest and validate data from other agencies or external entities in a secure manner. Automating this process can help agencies save time to focus on more strategic aspects of their mission.

Many researchers use MATLAB® from MathWorks, a programming and numeric computing platform, to analyze data, develop algorithms, and create models. As a researcher, you can leverage AWS to expand available computational resources right from your desktop or laptop. In this blog post, we walk through how to integrate MathWorks Cloud Center with AWS in order to accelerate scientific computation and innovation.

Modern applications built using microservices architectures improve customer experience by dramatically reducing the risk of failures in a web application. In this blog post, we present a sample AWS reference architecture of a microservices application built using an architecture framework based in AWS GovCloud (US), which can help support adherence to a Federal Risk and Authorization Management Program (FedRAMP) High Baseline.

Moodle is a popular open source learning management system (LMS). Many education institutions are deploying and running Moodle on a physical hardware or virtual machine (VM) environment. They are looking to improve the scalability of their Moodle application to simplify operations and monitoring, and also optimize operating costs. One way to approach this is to use containers technology. In this blog post, learn how to deploy and run Moodle using serverless containers technology on AWS.

To help our Australian customers, AWS provides pre-built conformance packs for the Australian Cyber Security Centre (ACSC) Essential Eight Maturity Model and the ACSC Information Security Manual (ISM). The ACSC’s Essential Eight was first published in 2017 and is a set of prioritised security mitigation strategies designed to help protect organisations against various security threats. In this blog post, I walk you through how to set up a conformance pack in AWS Config that is designed to help you implement and track the ASCS Essential Eight model.

In July 2021, the U.S. Department of Defense (DoD) released a cloud native access point (CNAP) reference design that follows zero trust architecture (ZTA) principles and provides a new approach to access mission owner (MO) applications. The DoD’s reference design discusses four core capabilities of CNAP: authenticated and authorized entities (C1), authorized ingress (C2), authorized egress (C3), and security monitoring and compliance enforcement (C4). In this blog post, we walk through how to establish the C2 component via a virtual internet access point (vIAP) with AWS. The proposed architectures can reduce operational cost and management overhead, while improving the accessibility, resiliency, and security of mission owner applications.

Data lakes are becoming increasingly common in many different workloads, and geospatial is no exception. In 2021, Amazon Web Services (AWS) announced geography and geohash support on Amazon Redshift, so geospatial analysts have the capability to quickly and efficiently query geohashed vector data in Amazon Simple Storage Service (Amazon S3). In this blog post, I walk through how to use geohashing with Amazon Redshift partitioning for quick and efficient geospatial data access, analysis, and transformation in your data lake.

To mitigate synthetic fraud, government agencies should consider complementing their rules-based improper payment detection systems with machine learning (ML) techniques. By using ML on a large number of disparate but related data sources, including social media, agencies can formulate a more comprehensive risk score for each individual or transaction to help investigators identify improper payments efficiently. In this blog post, we provide a foundational reference architecture for an ML-powered improper payment detection solution using AWS ML services.

In a data-dependent world, success belongs to the side with decision advantage: the ability to acquire data and make sense of a complex and adaptive environment, and act smarter and faster than the competition. Understanding global environments requires more than just more data – it requires live two- and three-dimensional maps, new support tools, improved processes, seamless connectivity, and better collaboration that can scale to the needs of the environment. This blog post explores how to address challenges of big data and accelerate time to data insights with machine learning with AWS Snowball Edge device deployment at the edge.