AWS Architecture Blog
Introducing the Snowflake and AWS Custom Lens for the AWS Well-Architected Framework
The Snowflake and AWS Custom Well-Architected Framework Lens brings together AWS Well-Architected best practices and Snowflake guidance into a single review experience, with integrated recommendations that reflect how the two services compose in production. In this post, we walk through each pillar, the three access points (AWS Management Console, Kiro, and Snowflake Cortex Code), and how to run your first review.
Automate medical record digitization with Amazon Bedrock Data Automation and AWS HealthLake
In this post, you learn how to build an automated, serverless pipeline that converts scanned PDF medical records into FHIR R4-compliant data using Amazon Bedrock Data Automation and AWS HealthLake. We walk through the architecture, explain how each AWS service connects to the next, show you what the pipeline looks like when it runs, and get you deployed in under 20 minutes.
Align your architecture backlog with Tech Roadmap Prioritization (TRP)
In this post, we show you how to run a one-hour prioritization session with your stakeholders, plot competing initiatives on a shared matrix by cost and impact and turn the result into an actionable architecture backlog – using a framework called Tech Roadmap Prioritization (TRP).
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.
Scaling oncology patient support: How New York Cancer and Blood Specialists transformed customer experience with AWS and Pronetx, now part of Caylent
This post details how NYCBS partnered with Amazon Web Services (AWS) and AWS partner Pronetx (now part of Caylent) to migrate to Amazon Connect Customer, the AWS cloud contact center service. The migration delivered a 54 percent improvement in patient enrollment and transformed the way NYCBS connects with the patients who need them most.
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.
Cyber resilience on AWS: A reference approach for recovery from ransomware and destructive events
Cyber resilience is the ability to recover workloads to a known-good state after an adversary has affected the environment. Prevention works to keep threat actors out and detection works to find them quickly. Cyber resilience focuses on recovery: restoring a trustworthy environment when backups, credentials, or parts of the infrastructure can no longer be assumed […]
How ALS GeoAnalytics LITHOLENS ™ revolutionizes core logging through machine learning with Amazon EKS
This post explores how ALS GeoAnalytics successfully deployed LITHOLENS ™ with Amazon Elastic Kubernetes Service (Amazon EKS) to scale model training and inference while minimizing cost.
How Synthesia optimizes generative AI video inference on Amazon EC2 G7e instances
This post introduces a video decoding optimization technique that we have ideated in collaboration with Synthesia Research Engineering team, which we call Asynchronous Frame Generation Pipeline. Adopting this technique allows you to overlap GPU compute, device-to-host (D2H) data transfer, and host-side post-processing. In this post, we apply this technique to the VAE decoder of a Wan video generation model as an example, where our benchmarks on G7e show increased GPU kernel utilization from 82% to 99.9%, in turn leading to an 8.2% decrease in latency (and increase in throughput) for video decoding. We expect this technique to benefit any customer with a chunked video generation pipeline that transfers frames to host memory.









