Category: Amazon EC2

After Rockdale County, Georgia was the victim of two cyber attacks, the jurisdiction turned to the cloud to strengthen the county’s security position. They worked with AWS Partner Tyler Technologies, Inc. to help with their migration, which not only enhanced data security and continuity of operations, but also reduced network downtime by 99 percent, while streamlining budgeting and reducing the IT staff’s burden.

The AWS Cloud gives you access to virtually unlimited infrastructure suitable for high performance computing (HPC) workloads. With HPC, you can remove long queues and waiting times so you don’t have to choose availability over performance. In this technical guide, learn how to use AWS ParallelCluster to set up and manage an HPC cluster in a flexible, elastic, and repeatable way.

SAS Viya is a highly available, cloud-native analytics platform. The latest version of SAS Viya on Amazon Elastic Kubernetes Service (Amazon EKS) allows customers to receive all of Kubernetes’ advantages without the trouble of maintaining their own Kubernetes infrastructure. Plus, customers also inherit AWS compliance controls, which can accelerate the journey to achieving FedRAMP authority to operate (ATO) in AWS US Regions. In this post, we show the key components of the SAS Viya architecture along with its core features to help customers on their journey to the cloud.

During the COVID-19 pandemic, educational institutions that operated on in-person model shifted many of their traditionally in-person operations and activities—including grading, assessments and testing, and admissions—to a virtual format, where many had never been before. Educational technology (EdTech) companies around the world used the cloud to help quickly create and scale to meet the needs of these academic institutions while maintaining a consistent and smooth student experience.

AWS Application Migration Service (MGN) is a highly automated lift-and-shift solution, which works by replicating your on-premises (physical or virtual) and/or cloud servers into your AWS account. When you’re ready, AWS MGN automatically converts and launches your servers on AWS so you can quickly benefit from the cost savings, productivity, resilience, and agility of the cloud. This guide teaches you how to migrate a content management system platform (CMS), based on an example with WordPress, running on a simulated on-premises environment to AWS Cloud, using MGN.

Moving to AWS helped The University of the West Indies, Open Campus (UWIOC) improve performance of systems and operational efficiency while optimizing costs. Learn how UWIOC migrated more than 70 virtual machines, 10 applications, and five networks, plus their Moodle learning management system (LMS) and the UWIOC website, while saving 50 percent total cost of ownership along the way.

Canada’s history is rich, but not without its scars. The need for documentation and analysis has never been greater. Library and Archives Canada (LAC) is the custodian of Canada’s distant past and recent history—and Amazon Web Services (AWS) is helping expand its reach.

University College London’s (UCL) virtual learning environment, built on the Moodle learning management system, is at the heart of its digital education infrastructure and used by students all over the world. Before migrating to Amazon Web Services (AWS), its system could handle 2,500 concurrent users. But when the pandemic drove schools and universities to predominantly online teaching, the UCL team wanted to support six times this amount in just 10 weeks. Here’s how they did it with AWS.

Using AWS, Edunation seamlessly responded to increasing demand during the COVID-19 pandemic. Edunation collaborates with top educational institutions across the Middle East and North Africa (MENA) region and provides all-in-one learning and school management solutions. Today, the EdTech is on a mission to push learning management systems (LMS) beyond virtual classrooms.

About 40 million MRI scans are performed in the United States every year. MRIs are a valuable part of diagnostic plans, but as they exist today, they may not always be a part of a patient’s care plan. A research team at the New York University (NYU) Langone Center set out to make MRIs more accessible for more patients by using artificial intelligence (AI), machine learning (ML), and the power of cooperative open data sharing.