AWS Public Sector Blog
Category: AWS CodeCommit
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.
Best practices for project management in the AWS Cloud
Amazon Web Services (AWS) employs project management principles to deliver public sector cloud outcomes. These principles drive successful service launches, new solutions, and workload migrations. Read this blog post to learn about the project management tools, references, and AWS Management Console tips that give public sector customers better project visibility, automate task management, and help accelerate project outcomes.
Building hybrid satellite imagery processing pipelines in AWS
In this blog post, learn how companies operating in AWS can design architectures that maximize flexibility so they can support both cloud and on-premises deployment use cases for their satellite imagery processing workloads with minimal modifications.
One small team created a cloud-based predictive modeling solution to improve healthcare services in the UK
How do you predict and prepare for your citizens’ health and wellness needs during the COVID-19 pandemic? Healthier Lancashire and South Cumbria Integrated Care System (ICS) quickly scaled a platform on AWS to support the 1.8 million people in their region with Nexus Intelligence, an interactive health intelligence application with a suite of predictive models against various measures of need and health outcomes. Nexus Intelligence not only supported the ICS response to the pandemic, but is expected to help reconfigure and re-invest in services to improve the health and well-being of the population and reduce health inequalities.
How to manage Amazon SageMaker code with AWS CodeCommit
To help protect investments on ML, government organizations can securely store ML source code. Storing Amazon SageMaker Studio code in an AWS CodeCommit repository enables you to keep them as standalone documents to reuse in the future. SageMaker Studio provides a single, web-based visual interface where you can perform all ML development steps required to prepare data and build, train, and deploy models. Read on to learn the steps to configure a git-based repository on CodeCommit to manage ML code developed with SageMaker.