Tag: technical how-to

Open data is reshaping how we understand and respond to global challenges. From climate change to disaster recovery, the ability to access and analyze large-scale geospatial datasets is critical for scientific research, policy-making, and real-world applications. Leading the charge are several open data initiatives designed to lower access barriers and accelerate innovation: Open Data on AWS, the Amazon Sustainability Data Initiative (ASDI), and the Maxar Open Data Program on AWS. Together, these programs demonstrate the power of cloud-enabled open data to democratize access to geospatial information, promote global collaboration, and drive real-world impact. In this post, we demonstrate how to explore and visualize these datasets using interactive web applications and Jupyter notebooks.

In this post, we explore how Amazon Q Business is transforming government organizations through secure, AI-powered assistance across various use cases—from public records management to workforce development. Its robust security features, compliance standards, and data privacy controls make it an ideal solution for government entities undergoing digital transformation.

Organizations are modernizing their incident response by using AWS capabilities alongside chat-based collaboration platforms such as Slack and Microsoft Teams. This shift helps streamline monitoring, enabling centralized awareness, real-time collaboration, and faster threat detection and mitigation. In this post, we demonstrate how Amazon Q Developer in chat applications transforms incident response and team coordination, with practical examples using Slack integration.

University central IT teams serve as the backbone of campus-wide technology operations, managing critical infrastructure, services, and security that power both academic and administrative functions. These teams are responsible for orchestrating complex cloud environments across multiple AWS accounts, making sure they meet institutional standards while enabling innovation across the campus community.

In this post, we provide step-by-step guidance for deploying Malcolm—an open source network traffic analysis suite—natively on Amazon Elastic Compute Cloud (Amazon EC2), using the on-demand compute, elasticity, and scalability of AWS to eliminate traditional infrastructure overhead. This approach is particularly beneficial for cost-conscious public sector (federal, state, and local), utility, and industrial customers who require network and security monitoring to deliver on their missions.

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. Whether a provider submits claims electronically or on paper, the claim could be adjudicated using the same process and analyzed the same way, saving both time and money. AI and ML services from AWS allow Medicaid agencies to create this streamlined solution. Moreover, AWS enables the adoption of solutions like this by providing no code or low code serverless services. Read this post to learn more

In this post, we discuss how to use datasets in the Registry of Open Data on AWS with Amazon Bedrock Knowledge Bases. With Amazon Bedrock Knowledge Bases, you can give foundation models (FMs) and agents contextual information from private and public data sources to deliver more relevant, accurate, and customized responses.

In this post, we explore how we’re transforming educational content alignment by combining the graph database capabilities of Amazon Neptune with large language models (LLMs) accessible in Amazon Bedrock.

This post demonstrates how TLS inspection in Network Firewall provides visibility into encrypted traffic, even when browsers implement Encrypted Client Hello (ECH) or when SNI fields contain modified information.

Many public sector agencies consist of multiple departments, each with their own functions. This can introduce administrative delays when processing incoming requests due to challenges such as needing to manually route the ever-growing volume of paperwork to the correct destination. This blog explores how Amazon Bedrock can be used to address these challenges by classifying documents based on their key topics and appropriately distributing them. In particular, we will focus on improving the efficiency of the freedom of information (FOI) request process, but this solution can be applied to various public sector use cases.