Tag: AWS GovCloud (US)

Zero trust in the US public sector has become critical, especially as cyber threats targeting government agencies grow more complex and sophisticated. In line with the federal mandate for zero trust architecture (ZTA) outlined in Executive Order M-22-09, government agencies are required to adopt a comprehensive security framework that continuously verifies trust for every access request. In this post, we demonstrate how Cisco Umbrella for Government, built on Amazon Web Services (AWS), plays a key role in ZTA by providing multi-layered security and granular visibility across on premises and AWS.

In this post, we explore how generative artificial intelligence (AI), powered by services such as Amazon Bedrock and Amazon SageMaker, can be harnessed to meet the unique challenges of AWS GovCloud (US). We highlight use cases that demonstrate the potential of generative AI to enhance efficiency, automate workflows, and extract insights—all within a secure, compliant framework.

The National Institutes of Health (NIH) has long maintained guidelines governing the responsible management of controlled access human genomic and phenotypic data maintained in NIH-designated data repositories. Recently, the NIH updated these guidelines to align with the NIST SP 800-171 security standard, which defines a comprehensive framework for securing Controlled Unclassified Information (CUI). In this blog post, we will explore the specifics of the updated NIH guidance and outline how Amazon Web Services (AWS) can help customers build a compliant environment to meet these requirements.

CMMC compliance will soon be a must-have for federal contractors, so they need to plan now for how to achieve it. The path towards compliance differs according to the level needed and the assessments involved. Fortunately, there is no shortage of resources available to help—including from Amazon Web Services (AWS) and its partners.

The Amazon Web Services (AWS) Modular Data Center (MDC) is a service that enables rapid deployment of AWS managed data centers for running location- or latency-sensitive applications in locations with limited infrastructure. It reduces deployment time in remote areas and supports up to five racks of AWS Outposts or AWS Snow Family devices. In this post, we guide you through the end-to-end process of deploying the MDC at your site.

How can technology leaders rapidly deliver responsible artificial intelligence-based innovation while aligning with the broad spectrum of strict regulatory requirements? The answer is simple: Amazon Web Services (AWS) GovCloud (US) provides the technology that underpins a solid foundation for securely and compliantly building and deploying AI capabilities. Read this post to learn more.

Peraton is a mission capability integrator and delivers enterprise IT around the world. They are also an Amazon Web Services (AWS) Premier Tier Services Partner with competencies in government, DevOps, and migration. Peraton’s IT infrastructure and technology strategy are designed to support the delivery of mission-critical services and solutions to its customers at a global scale. In this post, we explore how Peraton used AWS to migrate and build out a virtual data center in AWS GovCloud (US) Regions within a six-month time frame with an advanced and secure end-state architecture.

Anduril Industries, a defense technology company, has launched Alfred, an internal enterprise search chatbot powered by cutting-edge Retrieval-Augmented Generation (RAG) architecture. By using Amazon Web Services (AWS) services, such as Amazon SageMaker, Amazon Kendra, and Amazon DynamoDB, on the secure AWS GovCloud (US) Regions, Anduril has built a robust and scalable data infrastructure that can support Alfred’s growing knowledge needs.

In this post, we show you how you can push or pull your security telemetry data to the National Cybersecurity Protection System (NCPS) Cloud Log Aggregation Warehouse (CLAW) using Amazon Web Services (AWS) Simple Storage Service (Amazon S3) or third-party solutions.

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.