AWS Public Sector Blog

Tag: AWS CloudFormation

AWS branded background with text overlay that says "Mitigating inadvertent IPv6 prefix advertisement with AWS automation"

Mitigating inadvertent IPv6 prefix advertisement with AWS automation

As federal agencies migrate to the Trusted Internet Connections (TIC) 3.0 framework, they will use Amazon Web Services (AWS) to exit to the internet, bypassing the TIC network. This transition requires agencies to plan and coordinate migration activities to verify seamless IPv6 connectivity. Agencies need to coordinate advertising their IPv6 prefixes with AWS, using mechanisms like Bring your own IP addresses (BYOIP). The migration process could involve changes in routing policies, firewall rules, and security controls to accommodate the IPv6 prefix changes. Read this post to learn more.

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University of British Columbia Cloud Innovation Centre: Governing an innovation hub using AWS management services

In January 2020, Amazon Web Services (AWS) inaugurated a Cloud Innovation Centre (CIC) at the University of British Columbia (UBC). The CIC uses emerging technologies to solve real-world problems and has produced more than 50 prototypes in sectors like healthcare, education, and research. The Centre’s work has involved 300-plus AWS accounts across various groups, including external collaborators, UBC staff, students, and researchers. This post discusses the management of AWS in higher education institutions, emphasizing governance to securely foster innovation without compromising security and detailing policies and responsibilities for managing AWS accounts across projects and research.

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Hydrating the Natural History Museum’s Planetary Knowledge Base with Amazon Neptune and Open Data on AWS

The Natural History Museum (NHM) in London is a world-class visitor attraction and a leading science research center. NHM and Amazon Web Services (AWS) have partnered up to transform and accelerate scientific research by bringing together a broad range of biodiversity and environmental data types in one place for the first time. In an earlier post, we discussed NHM’s overall vision for using open data in combination with large-scale compute, data systems, and machine learning (ML) to create the Planetary Knowledge Base (PKB), a knowledge graph of global biodiversity. In this post, we focus on the underlying services and architecture that comprise the PKB.

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SoftwareOne boosts developer efficiency and streamlines code reviews using Amazon Bedrock

SoftwareOne, an Amazon Web Services (AWS) Premier Tier Services Partner and a global provider of end-to-end software and cloud technology solutions, addresses code review challenges with its automated solution, SummarAIze, powered by the generative artificial intelligence (generative AI) capabilities of Amazon Bedrock. This post provides an overview of SoftwareOne’s approach to building SummarAIze and its impact on the software development process.

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Using customer-provided ephemerides with AWS Ground Station

Amazon Web Services (AWS) Ground Station is a cloud-based service that provides you with an opportunity to perform communication sessions with your satellite without spending a fortune on your own ground station infrastructure. AWS Ground Station balances between providing a ready-made solution and tailoring the service to meet the unique needs of each customer. One of the ways to customize the service is to use customer-provided ephemerides (CPE) for antenna targeting.

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Satellite mission operations using artificial intelligence on AWS

Cognitive Space is a leading Amazon Web Services (AWS) Partner delivering intelligent automation to satellite constellation operations using the CNTIENT platform. The system uses AWS-powered artificial intelligence (AI) decision making to handle highly complex and dynamic satellite tasking requirements, and demanding mission requirements. This blog post provides technical guidance for building and operating mission operation centers (MOCs) on AWS.

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Improving customer experience for the public sector using AWS services

Citizens are increasingly expecting government to provide modern digital experiences for conducting online transactions. Market research tells us 63 percent of consumers see personalization as the standard level of service. This post offers various architectural patterns for improving customer experience for the public sector for a wide range of use cases. The aim of the post is to help public sector organizations create customer experience solutions on the Amazon Web Services (AWS) Cloud using AWS artificial intelligence (AI) services and AWS purpose-built data analytics services.

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Building compliant healthcare solutions using Landing Zone Accelerator

In this post, we explore the complexities of data privacy and controls on Amazon Web Services (AWS), examine how creating a landing zone within which to contain such data is important, and highlight the differences between creating a landing zone from scratch compared with using the AWS Landing Zone Accelerator (LZA) for Healthcare. To aid explanation, we use a simple healthcare workload as an example. We also explain how LZA for Healthcare codifies HIPAA controls and AWS Security Best Practices to accelerate the creation of an environment to run protective health information workloads in AWS.

AWS branded background design with text overlay that says "Building NHM London’s Planetary Knowledge Base with Amazon Neptune and the Registry of Open Data on AWS"

Building NHM London’s Planetary Knowledge Base with Amazon Neptune and the Registry of Open Data on AWS

The Natural History Museum in London is a world-class visitor attraction and a leading science research center. NHM and Amazon Web Services (AWS) have worked together to transform and accelerate scientific research by bringing together a broad range of UK biodiversity and environmental data types in one place for the first time. In this post, the first in a two-part series, we provide an overview of the NHM-AWS project and the potential research benefits.

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Use Landing Zone Accelerator on AWS customizations to deploy Cloud Intelligence Dashboards

In this post, you will learn how to deploy Amazon Web Services (AWS) Cloud Intelligence Dashboards (CID) using the Landing Zone Accelerator on AWS (LZA) solution. In doing so, you will learn how to customize your LZA deployment using the customizations-config.yaml file. By utilizing the LZA and CID together, you can streamline the deployment process, ensure compliance with best practices, and gain valuable insights into your cloud environment, ultimately leading to improved operational efficiency, enhanced security, and better-informed decision-making.