Category: Security, Identity, & Compliance

Spanish space-tech company IENAI SPACE put its cloud-based mission analysis platform, 360™, through the AWS Foundational Technical Review (FTR)—and came out stronger. In this post, we explore how the FTR process helped the team harden per-tenant data isolation and encryption, build a continuous software-supply-chain security pipeline, and formalize backup and recovery objectives, all while running on AWS.

In this post, we explore how Amazon Web Services (AWS) AI capabilities can transform constituent services and business operations. We also highlight some customer success stories and offer some practical advice on how to get started.

This post walks through what GeDaC built, the build decisions behind it, and why the pattern generalizes well beyond one lab.

This post shows you how to find those delegation failures in 30 minutes and what to do about them. It builds on the delegation model introduced in the Amazon Bedrock AgentCore companion post and turns it into an audit you can run today. This post also shows you how to enforce the boundaries you find on Amazon Web Services (AWS) with Amazon Bedrock AgentCore Policy, AWS Identity and Access Management (IAM), and Amazon Bedrock Guardrails.

This post demonstrates how to use Amazon Elastic Compute Cloud (Amazon EC2) instance attestation to produce cryptographically verifiable Amazon Machine Images (AMIs) for your DevSecOps platform and pipeline—the software factory that builds and delivers your workloads.

Analysts manually reviewing virtual reams of sensitive documents, looking for one key detail, need a more efficient way to search. They know generative AI must be able to do the job, but what they don’t know is whether they can apply generative AI to law enforcement data. You can, and Amazon Web Services (AWS) offers […]

This post, which details a collaboration between a national genomics research institute and Temus using Amazon Web Services (AWS), demonstrates the power of combining deep bioinformatics with advanced AI models and machine learning methods in a scalable AWS environment to uncover novel patterns in complex viral genomes. In this post, we explore the details of a scalable proof of concept (POC) pipeline built on AWS that uses an advanced genomic foundation model and unsupervised clustering to transform raw genomic sequences into signals for further research.

In this post, we translate pillars into a deployable cloud foundation, focusing on the key postures of security, identity management, governance, network design, resilience, continuity, auditability, and operational independence.

AI handles triage while analysts handle judgment. And, by coupling automated continuous monitoring with AI system connectivity, recovery time can speed up, resulting in fewer after-hours status calls. Your existing Amazon Web Services (AWS) environment already has access to the capabilities that can make this a reality.

In this post, we look at why these three make up the AWS CAF-AI perspectives EdTech leaders should mature first, and what building each one looks like in practice.