Category: Amazon EC2

Managing access to websites and safeguarding users from harmful content is a critical component of a layered cybersecurity approach, especially in educational settings. Schools and institutions of higher learning have a responsibility to provide a secure online experience for their students and staff. Traditionally, this has been accomplished through on-site web filtering appliances. Amazon Web Services ( AWS) Network Firewall allows customers to filter their outbound web traffic from on-premises environments based on fully qualified domain names (FQDN) or Server Name Indication (SNI) for encrypted traffic. This post will use AWS Client VPN to demonstrate routing and filtering traffic from external resources through Network Firewall.

Government agencies are increasingly using large language models (LLMs) powered by generative artificial intelligence (AI) to extract valuable insights from their data in the Amazon Web Services (AWS) GovCloud (US) Regions. In this guide, we walk you through the process of adapting LLMs to specific domains with parameter efficient fine-tuning techniques made accessible through Amazon SageMaker integrations with Hugging Face.

Digital engineering fundamentally relies on integrating data across model structures by using a digital thread – an underlying framework for integrating data from across traditionally siloed functions that create a consolidated view of the system’s data throughout its lifecycle. The cloud is integral to digital engineering by supporting collaboration across geographically dispersed organizations, automating workflows for data connectivity and trade space analysis in a reliable, scalable, and cost-effective manner. This post describes how Amazon Web Services (AWS) Partner General Dynamics Information Technology (GDIT) has used digital engineering in combination with secure and scalable AWS services, to deliver secure IT systems to a large defense program.

Government agencies are increasingly using large language models (LLMs) powered by generative artificial intelligence (AI) to extract valuable insights from their data in the Amazon Web Services (AWS) GovCloud (US) Regions. In this guide, we walk you through the process of hosting LLMs on Amazon Elastic Compute Cloud (Amazon EC2) instances, using the Hugging Face Text Generation Inference (TGI) Container (TGI) for serving custom LLMs.

Renaissance Learning is a global leader in the pre-K–12 education technology (EdTech) space. Renaissance delivers its products to 16 million students across the world, and its digital solutions are used in more than one-third of US schools and 100-plus countries. As part of its cloud consolidation strategy, Renaissance migrated DnA, its standards-based assessment creation and administration solution, from Google Cloud Platform (GCP) to Amazon Web Services (AWS). After migration, Renaissance realized performance, scalability, and security improvements, all while reducing cloud spend by 30 percent.

In 2022, Emory launched the AI.Humanity initiative to explore the societal impacts of artificial intelligence (AI) and influence its future development to serve humanity. Emory aims to be a leading advocate for ethical use of AI and a top destination for students and faculty seeking to understand and apply its transformative technologies. Read this blog post to learn how Emory uses Amazon Web Services (AWS) to support the computing needs of AI.Humanity.

AWS GovCloud (US) was architected to have isolation (both physically and logically) from other AWS partitions for compliance. For this reason, AWS services, used to privately interconnect virtual private cloud (VPC) hosted resources within the same partition like AWS PrivateLink, Amazon Virtual Private Cloud (Amazon VPC) peering, or AWS Transit Gateway peering, cannot span from AWS GovCloud (US) to commercial Regions natively by design. In this post, we will highlight four connectivity patterns customers can use to interconnect VPC hosted systems cross partition.

The Pacific Northwest National Laboratory (PNNL) developed Aether as a reusable framework for sharing data and analytics with sponsors and stakeholders. Aether is a mature cloud-centered framework designed using Amazon Web Services (AWS) serverless services to provide a cost-effective and reliable environment for a dozen projects currently deployed with the framework. Read this post to learn more about how Aether’s serverless-first approach is enabling disaster response and risk management.

Chaos engineering, often misunderstood as intentionally breaking the production environment, aligns with the Amazon Web Services (AWS) Well-Architected Reliability pillar. Its purpose is to methodically simulate real-world disruptions in a controlled manner, spanning service providers, infrastructure, workloads, and individual components. In this blog post, we show how Pearson PLC, an AWS education technology (EdTech) customer, successfully implemented resilient architectures through chaos engineering using AWS Fault Injection Service (FIS).

Amazon Web Services (AWS) hosted the AWS Sustainability Breakfast Briefing on February 20, 2024, in Dublin, Ireland, featuring a panel of sustainability experts from AWS customers and partners, as well as educational talks on important sustainability themes. The main takeaway is that sustainability transformation takes time – but every step along the journey can be meaningful. Read this blog post for a recap of key highlights from the briefing.