AWS Architecture Blog
Category: Technical How-to
Streaming CloudWatch metrics to VPC-based OpenTelemetry collectors using Lambda
In this post, we demonstrate an approach we used to address this challenge for a customer by implementing an AWS Lambda transformation function that streams Amazon CloudWatch metrics directly to internal OpenTelemetry collectors running within a VPC.
Building hybrid multi-tenant architecture for stateful services on AWS
In this post, we show you how to build a hybrid multi-tenant architecture that provides strong tenant isolation without requiring per-tenant AWS accounts. You learn how to configure Route 53 weighted routing to distribute traffic across multiple accounts, deploy Application Load Balancer listener rules for tenant-specific routing, create dedicated ECS clusters per tenant, and establish AWS PrivateLink connectivity to shared dependencies.
Build a multi-tenant configuration system with tagged storage patterns
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.
Automate safety monitoring with computer vision and generative AI
This post describes a solution that uses fixed camera networks to monitor operational environments in near real-time, detecting potential safety hazards while capturing object floor projections and their relationships to floor markings. While we illustrate the approach through distribution center deployment examples, the underlying architecture applies broadly across industries. We explore the architectural decisions, strategies for scaling to hundreds of sites, reducing site onboarding time, synthetic data generation using generative AI tools like GLIGEN, and other critical technical hurdles we overcame.
Streamlining access to powerful disaster recovery capabilities of AWS
In this blog post, we take a building blocks approach. Starting with the tools like AWS Backup to protect your data, we then add protection for Amazon Elastic Compute Cloud (Amazon EC2) compute using AWS Elastic Disaster Recovery (AWS DRS). Finally, we show how to use the full capabilities of AWS to restore your entire workload—data, infrastructure, networking, and configuration, using Arpio disaster recovery automation.
How Aigen transformed agricultural robotics for sustainable farming with Amazon SageMaker AI
In this post, you will learn how Aigen modernized its machine learning (ML) pipeline with Amazon SageMaker AI to overcome industry-wide agricultural robotics challenges and scale sustainable farming. This post focuses on the strategies and architecture patterns that enabled Aigen to modernize its pipeline across hundreds of distributed edge solar robots and showcase the significant business outcomes unlocked through this transformation. By adopting automated data labeling and human-in-the-loop validation, Aigen increased image labeling throughput by 20x while reducing image labeling costs by 22.5x.
AI-powered event response for Amazon EKS
In this post, you’ll learn how AWS DevOps Agent integrates with your existing observability stack to provide intelligent, automated responses to system events.
How Convera built fine-grained API authorization with Amazon Verified Permissions
In this post, we share how Convera used Amazon Verified Permissions to build a fine-grained authorization model for their API platform.
Secure Amazon Elastic VMware Service (Amazon EVS) with AWS Network Firewall
In this post, we demonstrate how to utilize AWS Network Firewall to secure an Amazon EVS environment, using a centralized inspection architecture across an EVS cluster, VPCs, on-premises data centers and the internet. We walk through the implementation steps to deploy this architecture using AWS Network Firewall and AWS Transit Gateway.
A scalable, elastic database and search solution for 1B+ vectors built on LanceDB and Amazon S3
In this post, we explore how Metagenomi built a scalable database and search solution for over 1 billion protein vectors using LanceDB and Amazon S3. The solution enables rapid enzyme discovery by transforming proteins into vector embeddings and implementing a serverless architecture that combines AWS Lambda, AWS Step Functions, and Amazon S3 for efficient nearest neighbor searches.









