AWS Architecture Blog
Category: Advanced (300)
AI-powered clinical trial eligibility and safety using Amazon Bedrock AgentCore
AI agents built on Amazon Bedrock AgentCore help clinical trial teams make fast, accurate enrollment decisions while keeping clinicians in control. This post shows how to architect an eligibility and safety screening agent using AWS HealthLake, AgentCore, and AgentCore Evaluations.
Consistency is the new latency: AI at the data layer
As AI agents move from chatbots to taking action, their reliability depends on the consistency of the data layer beneath them. This post examines how replication lag poisons an agent’s context and shows how to match Amazon Aurora, Amazon DynamoDB, and Amazon Keyspaces replication models to each task’s consistency requirements.
Recovery strategies to meet data residency requirements
Learn three strategies for achieving disaster recovery while meeting data residency requirements. Ranging from encryption-based controls on multi-Region replication to fully in-country architectures, these patterns help you balance recovery objectives with regulatory constraints.
S&P Global’s innovative disaster recovery strategy using Amazon FSx for NetApp ONTAP snapshots
In this post, we explain how S&P Global Market Intelligence implemented an innovative disaster recovery solution for their Capital IQ platform using Amazon FSx for NetApp ONTAP. This solution enables immediate failover to read-only mode in a secondary region within 15 minutes, followed by full read-write recovery when needed. This approach achieves reduction in failover time while maintaining data consistency for global financial operations.
Building highly available Oracle databases with Amazon FSx for NetApp ONTAP
This post shows how to build a highly available Oracle database architecture using FSxN shared storage, Auto Scaling groups with dynamic AMI updates, and serverless orchestration to help reduce recovery times with current configurations.
Automating contract intelligence with Doczy.ai™ on AWS
In this post, we show you how Doczy.ai™ uses generative AI on AWS to automate contract intelligence at scale, transforming unstructured documents into structured, actionable insights, so organizations can automate critical business processes and unlock the full value of their data.
Building a scalable user search layer on top of Amazon Cognito
In this post, we show how to build a comprehensive scalable user search layer on top of Amazon Cognito using AWS Lambda, Amazon DynamoDB, and Amazon OpenSearch Service.
Build a multi-tenant configuration system with tagged storage patterns
In this post, we demonstrate how you can build a scalable, multi-tenant configuration service using the tagged storage pattern, an architectural approach that uses key prefixes (like tenant_config_ or param_config_) to automatically route configuration requests to the most appropriate AWS storage service. This pattern maintains strict tenant isolation and supports real-time, zero-downtime configuration updates through event-driven architecture, alleviating the cache staleness problem.
Automate safety monitoring with computer vision and generative AI
This post describes a solution that uses fixed camera networks to monitor operational environments in near real-time, detecting potential safety hazards while capturing object floor projections and their relationships to floor markings. While we illustrate the approach through distribution center deployment examples, the underlying architecture applies broadly across industries. We explore the architectural decisions, strategies for scaling to hundreds of sites, reducing site onboarding time, synthetic data generation using generative AI tools like GLIGEN, and other critical technical hurdles we overcame.
AI-powered event response for Amazon EKS
In this post, you’ll learn how AWS DevOps Agent integrates with your existing observability stack to provide intelligent, automated responses to system events.









