Category: Technical How-to

Electronic notifications of patient events are a vital mechanism for care providers to improve care coordination and promote appropriate follow-up care in a timely manner. This post shows how a combination of Amazon Web Services (AWS) technologies, like AWS Lambda, Amazon Comprehend Medical, and AWS Fargate, can effectively manage and deliver actionable data to help healthcare customers deliver electronic notifications in a secure and efficient way.

Moodle is an open-source learning management system (LMS). Moodle has more than 300 million users worldwide across both academic and enterprise organizations, and is the world’s most widely used learning platform. There are many ways to get started with Moodle on AWS. In this blog post, I focus on how to scale and optimize Moodle once you are already serving students. In this case, you may need to deal with migrating data from an existing platform and making sure the new environment caters to thousands of students, and still be cost-effective — we cover additional considerations in this walkthrough.

As organizations mature in their cybersecurity capabilities, they are looking to try and leverage automation to reduce the operational burden of alerting, detecting, and responding to threats. This blog post walks through how to combine findings from disparate security systems into a single operational view to help analysts identify, respond, and remediate existing threats while maintaining a dynamic response platform that scales with their environment.

The AWS Migration Evaluator can help organizations with VMware fleets by collecting detailed data on VM (virtual machine) usage and using that to prepare a business case for moving to the cloud and estimate the cost of migration. However, sensitive network data collected by the Migration Evaluator, such as system names and IP addresses, cannot leave highly secured and regulated organisations. In this blog post, learn how a simple python script can anonymize AWS Migration Evaluator usage data, allowing it to be uploaded even in highly regulated environments.

Terabytes of Earth Observation (EO) data are collected each day, quickly leading to petabyte-scale datasets. By bringing these datasets to the cloud, users can use the compute and analytics resources of the cloud to reliably scale with growing needs. In this post, we show you how to set up a Pangeo solution with Kubernetes, Dask, and Jupyter notebooks step-by-step on Amazon Web Services (AWS), to automatically scale cloud compute resources and parallelize workloads across multiple Dask worker nodes.

Several smart cities use FIWARE, an open source framework supporting the development of smart solutions. FIWARE leverages sensing data from Internet of Things (IoT) devices, then collects, stores, and analyzes data with an API call. One FIWARE component, Orion Context Broker, gathers context information from diverse sources such as mobile apps, IoT devices, and social networking services, and manages the lifecycle of this context information, from registrations, updates, queries, and subscriptions. In this blog post, we address building Orion Context Broker on AWS. Learn how to deploy Orion Context Broker and Cygnus on AWS with AWS Cloud Development Kit (AWS CDK) and Docker Compose quickly.

In this blog post series on getting started building a data lake for healthcare with AWS, I focus on improving the security posture of our example build by incorporating the relatively new Attribute Based Access Control (ABAC) feature of Amazon Cognito. This helps to both streamline and improve the granularity of access control for various user profiles connected to our data lake scenario.

With Amazon Connect, nonprofits are able to build a robust, scalable omnichannel cloud contact center to provide reliable, secure, and cost-effective services to their community, all without needing to provision any underlying infrastructure. In this blog, learn how to leverage AWS CloudFormation templates to quickly and simply set up Amazon Connect.

Data is an invaluable asset in the world of nonprofits. In this blog post, we offer a technical walkthrough to learn how nonprofits of all sizes can use Amazon QuickSight to quickly create interactive dashboards with the help of machine learning, providing a self-service way to effectively consume and analyze data without writing any code or having to worry about infrastructure.

Discovery Education (DE) provides standards-aligned digital curriculum resources, engaging content, and professional learning for K12 classrooms. Learn how they worked with AWS to enhance its K12 learning platform with machine learning (ML) capabilities.