AWS Public Sector Blog

Tag: technical how-to

Support FedRAMP and CMMC compliance with the Landing Zone Accelerator on AWS

Support FedRAMP and CMMC compliance with the Landing Zone Accelerator on AWS

Some US federal agencies and those who collaborate with them must support an automated, secure, and scalable multi-account cloud environment that meets Federal Risk and Authorization Management Program (FedRAMP) and Cybersecurity Maturity Model Certification (CMMC) standards. To support these needs, AWS customers and partners can deploy the Landing Zone Accelerator (LZA) on AWS. Recently, AWS worked with Coalfire, a FedRAMP-approved third-party assessment organization (3PAO) and AWS Partner, to assess and verify the LZA solution.

Implement a secure, serverless GraphQL architecture in AWS GovCloud (US) to optimize API flexibility and efficiency

Implement a secure, serverless GraphQL architecture in AWS GovCloud (US) to optimize API flexibility and efficiency

GraphQL is a query language and server-side runtime system for application programming interfaces (APIs) that prioritizes giving clients exactly the information they request and no more. GraphQL can help public sector customers focus on their data and provide ways to explore the data in their APIs. Learn a reference architecture using serverless technologies that you can use to build GraphQL-enabled solutions in the AWS GovCloud (US) Regions to unify data access in real-time and simplify operations.

Creating agentless outbound campaigns to support Medicaid unwinding efforts

Creating agentless outbound campaigns to support Medicaid unwinding efforts

With state Medicaid agencies (SMAs) contacting all their members, contact centers must scale to meet increased demand—however, staffing shortages can make this outreach and call support difficult. SMAs can support staff members and make sure members get their communications needs met by using AWS and cloud technology to introduce automation into their outreach process. Learn how to deploy a serverless outbound campaign to meet Medicaid unwinding outreach needs and support agency staff members by streamlining the outreach process.

Extracting, analyzing, and interpreting information from Medicaid forms with AWS

Extracting, analyzing, and interpreting information from Medicaid forms with AWS

What if paper forms could be processed at the same speed as digital forms? What if their contents could be automatically entered in the same database as the digital forms? Medicaid agencies could analyze data in near real time and drive actionable insights on a single dashboard. By using artificial intelligence (AI) and machine learning (ML) services from AWS, Medicaid agencies can create this streamlined solution. In this walkthrough, learn how to extract, analyze, and interpret relevant information from paper-based Medicaid claims forms.

How to store historical geospatial data in AWS for quick retrieval

How to store historical geospatial data in AWS for quick retrieval

Learn how to store historical geospatial data, such as weather data, on AWS using Amazon DynamoDB. This approach allows for virtually unlimited amounts of data storage combined with query performance fast enough to support an interactive UI. This approach can also filter by date or by location, and enables time- and cost- efficient querying.

Using Amazon IVS for turnkey town halls

Many nonprofit organizations need to provide their donors, members, and beneficiaries with relevant information that they can access from anywhere. Over the past few years, nonprofit organizations have seen positive results by hosting live town hall events in which members can receive important information and ask questions. In this walkthrough, learn how to set up Amazon IVS to build a turnkey live-streaming platform that integrates into an existing website.

Optimizing your nonprofit mission impact with AWS Glue and Amazon Redshift ML

Nonprofit organizations focus on a specific mission to impact their members, communities, and the world. In the nonprofit space, where resources are limited, it’s important to optimize the impact of your efforts. Learn how you can apply machine learning with Amazon Redshift ML on public datasets to support data-driven decisions optimizing your impact. This walkthrough focuses on the use case for how to use open data to support food security programming, but this solution can be applied to many other initiatives in the nonprofit space.

Building a team knowledge base with Amazon Lightsail

Building an organized system for common information—such as addresses, phone numbers, purchasing account numbers, a curated and annotated literature section, lab recipes and protocols, meeting schedules, and links to commonly used online tools—can prove extremely valuable for professors and their teams. Building this knowledge base on AWS with Amazon Lightsail can save hours of administration and maintenance time, while providing additional control and flexibility for remote access. In this blog post, learn how to set up a content management system (CMS) using Lightsail, including how to manage basic network security, backup, and upgrades, to build a knowledge base for your lab, agency, startup, or other team-based environment.

Decrease geospatial query latency from minutes to seconds using Zarr on Amazon S3

Decrease geospatial query latency from minutes to seconds using Zarr on Amazon S3

Geospatial data, including many climate and weather datasets, are often released by government and nonprofit organizations in compressed file formats such as the Network Common Data Form (NetCDF) or GRIdded Binary (GRIB). As the complexity and size of geospatial datasets continue to grow, it is more time- and cost-efficient to leave the files in one place, virtually query the data, and download only the subset that is needed locally. Unlike legacy file formats, the cloud-native Zarr format is designed for virtual and efficient access to compressed chunks of data saved in a central location such as Amazon S3. In this walkthrough, learn how to convert NetCDF datasets to Zarr using an Amazon SageMaker notebook and an AWS Fargate cluster and query the resulting Zarr store, reducing the time required for time series queries from minutes to seconds.

Using machine learning to customize your nonprofit’s direct mailings

Many organizations perform direct mailings, designed to support fundraising or assist with other efforts to help further the organization’s mission. Direct mailing workflows can use everything from a Microsoft Word mail merge to utilizing a third-party mailing provider. By leveraging the power of the cloud, organizations can take advantage of capabilities that might otherwise be out of reach, like customized personalization at scale. In this walkthrough, learn how organizations can utilize machine learning (ML) personalization techniques with AWS to help drive better outcomes on their direct mailing efforts.