AWS Architecture Blog
Category: *Post Types
How Salesforce migrated from Cluster Autoscaler to Karpenter across their fleet of 1,000 EKS clusters
This blog post examines how Salesforce, operating one of the world’s largest Kubernetes deployments, successfully migrated from Cluster Autoscaler to Karpenter across their fleet of 1,000 plus Amazon Elastic Kubernetes Service (Amazon EKS) clusters.
How BASF’s Agriculture Solutions drives traceability and climate action by tokenizing cotton value chains using Amazon Managed Blockchain
BASF Agricultural Solutions combines innovative products and digital tools with practical farmer knowledge. This post explores how Amazon Managed Blockchain can drive a positive change in the agricultural industry by tokenizing food and cotton value chains for traceability, climate action, and circularity.
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.
Architecting for AI excellence: AWS launches three Well-Architected Lenses at re:Invent 2025
At re:Invent 2025, we introduce one new lens and two significant updates to the AWS Well-Architected Lenses specifically focused on AI workloads: the Responsible AI Lens, the Machine Learning (ML) Lens, and the Generative AI Lens. Together, these lenses provide comprehensive guidance for organizations at different stages of their AI journey, whether you’re just starting to experiment with machine learning or already deploying complex AI applications at scale.
Announcing the updated AWS Well-Architected Generative AI Lens
We are delighted to announce an update to the AWS Well-Architected Generative AI Lens. This update features several new sections of the Well-Architected Generative AI Lens, including new best practices, advanced scenario guidance, and improved preambles on responsible AI, data architecture, and agentic workflows.
Announcing the updated AWS Well-Architected Machine Learning Lens
We are excited to announce the updated AWS Well-Architected Machine Learning Lens, now enhanced with the latest capabilities and best practices for building machine learning (ML) workloads on AWS.
Know before you go – AWS re:Invent 2025 guide to Well-Architected and Cloud Optimization sessions
Are you ready to maximize your Well-Architected and Cloud Optimization learning and networking time at re:Invent 2025? We have put together this comprehensive guide to help you plan your schedule and make the most of the Well-Architected and cloud optimization sessions available this year. These sessions will deliver the practical guidance your teams need to lead strategic cloud initiatives, design next-generation architectures, optimize costs, or secure AI-powered systems.
Modernization of real-time payment orchestration on AWS
The global real-time payments market is experiencing significant growth. According to Fortune Business Insights, the market was valued at USD 24.91 billion in 2024 and is projected to grow to USD 284.49 billion by 2032, with a CAGR of 35.4%. Similarly, Grand View Research reports that the global mobile payment market, valued at USD 88.50 […]
Build resilient generative AI agents
Generative AI agents in production environments demand resilience strategies that go beyond traditional software patterns. AI agents make autonomous decisions, consume substantial computational resources, and interact with external systems in unpredictable ways. These characteristics create failure modes that conventional resilience approaches might not address. This post presents a framework for AI agent resilience risk analysis […]
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.








