AWS Architecture Blog

Building resilient real-time streaming workers with Amazon DynamoDB leases

Building resilient real-time streaming workers with Amazon DynamoDB leases

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.

Testing Application Resilience with Amazon SQS and AWS Fault Injection Service

Testing application resilience with Amazon SQS and AWS Fault Injection Service

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.

Validating multi-Region DR for Terraform Enterprise with AWS FIS

Validating multi-Region DR for Terraform Enterprise with AWS FIS

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.

MCP went stateless. Is your AWS MCP Server Deployment Well-Architected?

MCP went stateless: Is your AWS MCP server deployment well-architected?

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.

Closing the AI agent trust gap with graduated autonomy

Closing the AI agent trust gap with graduated autonomy

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.

How a global payment processor preserved AWS RAM shares and Lake Formation permissions during an AWS Organizations migration

How a global payment processor preserved AWS RAM shares and Lake Formation permissions during an AWS Organizations migration

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.

Build a unified AI agent architecture with DynamoDB and Bedrock

Build a unified AI agent architecture with DynamoDB and Bedrock

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.

How AgentFlo built AI sales agents with Amazon Bedrock AgentCore – Part 2

How AgentFlo built AI sales agents with Amazon Bedrock AgentCore – Part 2

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.