ReadyOn runs a multi-tenant platform on Amazon EKS that handles highly sensitive enterprise data. This post describes their Four Walls model: four independent layers of tenant isolation combining Kubernetes namespaces, Karpenter node pools, Amazon VPC security groups, and per-tenant Amazon Aurora databases for zero-trust defense in depth.
Learn how researchers at CSIRO, Australia's national science agency, built Serverless Beacon (sBeacon), a scalable serverless solution for securely querying genomic variant data on AWS. sBeacon implements the GA4GH Beacon standard using Amazon S3, AWS Lambda, Amazon DynamoDB, and Amazon Athena to support production-scale clinical and research applications.
Equinix, the world's digital infrastructure company, built a shared services architecture on Amazon EKS to eliminate the operational sprawl of its self-managed Kubernetes environment. Learn how a multi-account North Star architecture centralized governance and shared services, delivering 4x faster deployments and 40% less operational overhead.
A hybrid cloud architecture pattern for modernizing medical imaging on AWS. Learn how multi-hospital networks can centralize PACS archives, enable cross-facility interoperability, and use Amazon S3 storage tiers to manage cost and retention at scale.
Learn how DHI Group partnered with AWS to move generative AI workloads from idea to production using a structured hackathon. This post covers the Hackathon Acceleration Package, the winning ClearanceJobs and AgileATS agentic architecture on Amazon Bedrock AgentCore, and the principles that make hackathons a repeatable path to production.
Combine zero-shot forecasting with Amazon Chronos2 and multi-agent orchestration on Amazon Bedrock AgentCore to turn demand forecasts into validated purchase orders. No per-product model training, with business rules, auditability, and cost that scales to zero.
Real-time streaming workers that hold hundreds of persistent WebSocket connections lose data when a worker fails. Learn how to build a WebSocket fleet management system on Amazon ECS and AWS Fargate that uses Amazon DynamoDB conditional writes as a distributed lease to track ownership, fail over automatically, and deploy with low downtime.
Learn how to use AWS Fault Injection Service and AWS Systems Manager Automation to run progressive chaos experiments against Amazon SQS queues. Validate that your retry logic, circuit breakers, and dead-letter queues actually work under failure before a real outage hits production.
Learn how AWS, HashiCorp, and Athenahealth designed and chaos-tested a multi-Region disaster recovery strategy for Terraform Enterprise on AWS. This post walks through three-phase AWS Fault Injection Service experiments across Amazon EC2, Aurora, and Amazon S3, the 12-14 minute recovery times achieved, and the state file dependency pitfall to avoid.
Learn how to build a hybrid cloud orchestration solution that manages distributed on-premises infrastructure at scale using AWS serverless technologies and Amazon EKS Anywhere. Part 1 covers the core event-driven architecture patterns for automating server lifecycle and cluster management across hundreds of sites.
On July 28, 2026, MCP made its protocol core stateless, removing the initialize handshake and session header. This post maps the MCP 2026-07-28 specification to the AWS Well-Architected Agentic AI Lens, pillar by pillar, and shows why the stateless design lets you delete the sticky sessions and session stores your MCP servers needed on AWS.
Gallup transformed 90 years of workplace science into Gallup AI, a generative AI assistant powered by Amazon Bedrock that delivers real-time, personalized coaching to leaders directly within the Gallup Access application.
Most teams give AI agents either full access or read-only, leaving value unused or risk unmanaged. This post describes graduated autonomy, an architectural pattern in which agents earn expanded permissions through sustained reliability and lose them when performance degrades, built on Amazon Bedrock AgentCore, Amazon DynamoDB, and AWS CodePipeline.
When AWS accounts move between organizations, organization-bound AWS RAM resource shares break and control-plane access is lost. Learn how a global payment processor used temporary bridge shares to preserve AWS Lake Formation permissions across a 382-account AWS Organizations migration, then restored the original shares as the durable source of truth.
With native vector search in Amazon DynamoDB, you can store vector embeddings alongside your operational data in a single table. This post shows how to build a unified AI agent architecture where an Amazon Bedrock agent uses one DynamoDB table for both structured lookups and semantic search, with a DynamoDB Streams pipeline that keeps embeddings in sync.
Part 2: how AgentFlo built trusted, reliable AI sales agents on Amazon Bedrock AgentCore and AWS serverless architecture. Learn the three-layer guardrails, grounded data foundation, and end-to-end observability behind a +12% net revenue uplift, plus what's next for real-time voice and server-side tool execution.
Learn how AgentFlo built always-on AI sales agents on Amazon Bedrock AgentCore and the Strands Agents SDK. Part 1 covers three pillars of production-grade agents—velocity, standardization, and scalability—including recipe-based deployment, tool routing through AgentCore Gateway, and elastic, stateful commerce conversations.
Clario, part of Thermo Fisher Scientific, uses Amazon Bedrock and Amazon Textract to automatically detect protected health information (PHI) and personally identifiable information (PII) across thousands of DICOM image slices in clinical trials, covering both metadata tags and text burned into the image pixels.
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.
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.