ReadyOn在Amazon EKS上的四层租户隔离架构实践
ReadyOn在Amazon EKS上运行处理高敏感企业数据的多租户平台。该公司提出了“四面墙”(Four Walls)隔离模型,通过结合Kubernetes命名空间、Karpenter节点池、Amazon VPC安全组以及按租户独立的Amazon Aurora数据库,构建了四个相互独立的租户隔离层,实现针对多租户环境的零信任纵深防御体系。
ReadyOn在Amazon EKS上运行处理高敏感企业数据的多租户平台。该公司提出了“四面墙”(Four Walls)隔离模型,通过结合Kubernetes命名空间、Karpenter节点池、Amazon VPC安全组以及按租户独立的Amazon Aurora数据库,构建了四个相互独立的租户隔离层,实现针对多租户环境的零信任纵深防御体系。
澳大利亚国家科学机构CSIRO基于AWS开发了无服务器架构解决方案Serverless Beacon(sBeacon),旨在实现基因组变异数据的安全与高扩展查询。该方案遵循GA4GH Beacon标准,集成了Amazon S3、AWS Lambda、Amazon DynamoDB和Amazon Athena等云服务,有效优化了查询成本,可支持生产级临床和科研应用场景。
全球数字基础设施巨头 Equinix 在 Amazon EKS 上构建了共享服务架构,以解决此前自建 Kubernetes 环境带来的运维蔓延难题。通过采用多账户 North Star 架构实现集中化治理与服务共享,Equinix 将应用部署速度提升了 4 倍,同时将基础设施运维开销降低了 40%,有效提升了多集群管理的扩展性与运维效率。
本文介绍了在AWS上实现医疗影像现代化的混合云架构模式。该方案阐述了多医院网络如何集中管理PACS档案、实现跨机构互操作性,并借助Amazon S3分层存储在大规模场景下有效优化存储成本与数据保留生命周期。
DHI Group与AWS合作,通过结构化黑客松模式推动生成式AI工作负载从概念快速走向生产环境。文章详细介绍了其“黑客松加速包”、基于Amazon Bedrock AgentCore构建的ClearanceJobs与AgileATS智能体架构,以及如何将黑客松打造成一套可重复的AI项目落地机制与工程实践原则。
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.