Category: Learning Levels

In this post, we walk through the legacy architecture challenges, the stateless streaming solution, key implementation patterns, and performance results—a pattern you can apply if you’re building high-traffic APIs that aggregate data from multiple backend sources.

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.

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.

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.

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.

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.

This post extends IBM’s approach to real-time KYC validation using generative AI, as previously discussed in the post IBM Digital KYC on AWS uses Generative AI to transform Client Onboarding and KYC Operations. It transforms compliance operations through autonomous decision-making and intelligent automation using agentic AI, event-driven architecture, and AWS serverless services. The solution addresses the fundamental limitations of traditional rule-based systems. It provides autonomous decision-making, dynamic adaptation, and intelligent automation that transforms compliance operations.

This post explores how PACIFIC enables multi-tenant, sovereign PCF exchange on the Catena-X data space using Amazon Elastic Container Service (Amazon ECS) on AWS Fargate, Amazon Cognito, and AWS Identity and Access Management (IAM) to deliver measurable environmental impact and competitive advantage in a carbon-conscious marketplace.

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.

In this post, we walk through the new installation experience, demonstrate three deployment methods (console, CLI, and Terraform), and show how features like multi-instance-type deployment and native node affinity give you fine-grained control over inference scheduling