Category: Compute

As governments worldwide seek to modernize their services, secure and scalable digital identity systems are becoming essential infrastructure. Through a combination of AWS Outposts, digital identity solutions like Modular Open Source Identity Platform (MOSIP), and innovative architectures that couple cloud capabilities with data residency requirements, governments can build digital identity systems that are reliable, resilient, and ready for the future. Read this post to learn more.

In modern cloud environments, organizations need efficient ways to manage and deploy multiple microservices while maintaining individual service autonomy and deployment flexibility. This is particularly important for complex solutions like child support systems that require both reliability and agility in their deployment processes. Voyatek offers an open-source, cloud-based child support solution that leverages a microservices architecture powered by AWS. Read this post to learn more.

In this post, we provide step-by-step guidance for deploying Malcolm—an open source network traffic analysis suite—natively on Amazon Elastic Compute Cloud (Amazon EC2), using the on-demand compute, elasticity, and scalability of AWS to eliminate traditional infrastructure overhead. This approach is particularly beneficial for cost-conscious public sector (federal, state, and local), utility, and industrial customers who require network and security monitoring to deliver on their missions.

In an era where scientific discovery transcends borders, cloud computing is helping advance how researchers collaborate and innovate across the globe. Now available for download, The Value of Utilizing Cloud Service Providers for Open Science Research report—produced by Hyperion Research and sponsored by AWS— explores how and why researchers use cloud to accelerate open science research. Read this post to learn more.

In this post, you will learn how AWS technologies support the entire autonomous system lifecycle from AI-powered design and virtual prototyping in pre-deployment, to edge computing through services like AWS IoT Core and AWS IoT Greengrass and related solution guidance like Tactical Edge Application Deployment on AWS and Cloud Edge Global Access (CEGA) during deployment, through real-time mission operations, and finally to post-mission evolution using secure over-the-air updates and predictive maintenance.

The University of Minnesota Athletics Department had access to a lot of data, but lacked a way to bring it together. Even answering simple questions, like how many tickets were sold and who received them, required hours of cross-platform data wrangling. In less than a year, the department replaced that complexity with a scalable data lake built on AWS. The new data architecture—which gives the department full visibility into ticketing transactions and digital behavior—was built by a small internal team, without requiring a complete overhaul of their existing systems.

This significant growth in military unmanned aerial vehicles, which serve as a proxy for the broader autonomous systems market, underscores the urgent need for scalable, secure, and efficient software deployment solutions. As the number of autonomous platforms increases, so does the complexity of managing their software systems. In response to this growing challenge, Shield AI and AWS have collaborated and successfully demonstrated a scalable architecture and proof of concept (PoC) that addresses challenges often seen when deploying autonomy software and machine learning algorithms onto autonomous systems.

Learning Upgrade worked with AWS to modernize its platform and ultimately migrated fully to the cloud. This strategic shift empowered Learning Upgrade to scale globally, respond faster to new opportunities, and better serve learners in dynamic, resource-constrained environments. Read this post to learn more.

In this post, we demonstrate how to use the advanced malware detection features of Amazon GuardDuty to uncover malicious and suspicious files compromising your Amazon Elastic Compute Cloud (Amazon EC2) instances. We use the investigative capabilities of Amazon Detective to gain deeper insights into the security event. After the key questions about the security event are addressed, we outline steps to remediate the potentially compromised EC2 instance.

This post demonstrates how to enhance security and compliance in an isolated SageMaker JupyterLab environment by implementing two key customizations: configuring download restrictions and implementing secure Python package installation through AWS CodeArtifact.