AWS Architecture Blog
Category: Learning Levels
Simplify multi-tenant encryption with a cost-conscious AWS KMS key strategy
In this post, we explore an efficient approach to managing encryption keys in a multi-tenant SaaS environment through centralization, addressing challenges like key proliferation, rising costs, and operational complexity across multiple AWS accounts and services. We demonstrate how implementing a centralized key management strategy using a single AWS KMS key per tenant can maintain security and compliance while reducing operational overhead as organizations scale.
How Karrot built a feature platform on AWS, Part 1: Motivation and feature serving
This two-part series shows how Karrot developed a new feature platform, which consists of three main components: feature serving, a stream ingestion pipeline, and a batch ingestion pipeline. This post starts by presenting our motivation, our requirements, and the solution architecture, focusing on feature serving.
How Karrot built a feature platform on AWS, Part 2: Feature ingestion
This two-part series shows how Karrot developed a new feature platform, which consists of three main components: feature serving, a stream ingestion pipeline, and a batch ingestion pipeline. This post covers the process of collecting features in real-time and batch ingestion into an online store, and the technical approaches for stable operation.
Deploy LLMs on Amazon EKS using vLLM Deep Learning Containers
In this post, we demonstrate how to deploy the DeepSeek-R1-Distill-Qwen-32B model using AWS DLCs for vLLMs on Amazon EKS, showcasing how these purpose-built containers simplify deployment of this powerful open source inference engine. This solution can help you solve the complex infrastructure challenges of deploying LLMs while maintaining performance and cost-efficiency.
How Zapier runs isolated tasks on AWS Lambda and upgrades functions at scale
In this post, you’ll learn how Zapier has built their serverless architecture focusing on three key aspects: using Lambda functions to build isolated Zaps, operating over a hundred thousand Lambda functions through Zapier’s control plane infrastructure, and enhancing security posture while reducing maintenance efforts by introducing automated function upgrades and cleanup workflows into their platform architecture.
How Scale to Win uses AWS WAF to block DDoS events
In this post, you’ll learn how Scale to Win configured their network topology and AWS WAF to protect against DDoS events that reached peaks of over 2 million requests per second during the 2024 US presidential election campaign season. The post details how they implemented comprehensive DDoS protection by segmenting human and machine traffic, using tiered rate limits with CAPTCHA, and preventing CAPTCHA token reuse through AWS WAF Bot Control.
Amazon Bedrock baseline architecture in an AWS landing zone
In this post, we explore the Amazon Bedrock baseline architecture and how you can secure and control network access to your various Amazon Bedrock capabilities within AWS network services and tools. We discuss key design considerations, such as using Amazon VPC Lattice auth policies, Amazon Virtual Private Cloud (Amazon VPC) endpoints, and AWS Identity and Access Management (IAM) to restrict and monitor access to your Amazon Bedrock capabilities.
Build a multi-Region AWS PrivateLink backed service with seamless failover
This post demonstrates how the Issuer Solutions business of Global Payments, as a service provider, implemented cross-Region failover for an AWS PrivateLink backed service exposed to their customers. Their solution enables failover to a secondary Region without customer coordination, reducing Recovery Time Objective (RTO).
How Stellantis streamlines floating license management with serverless orchestration on AWS
In this post, we explore a unique scenario where an ISV, unable to provide a floating license option for cloud usage, worked with Stellantis to develop an alternative solution. This approach, implemented with the ISV’s permission, treats named user licenses as if they were floating, automatically assigning and removing them based on the state of user workbench instances.
Optimizing fleet operations using Amazon SageMaker AI and Amazon Bedrock
In this post, we’ll explore how to maximize the value of dashcam footage through best practices for implementing and managing Computer Vision systems in commercial fleet operations. We’ll demonstrate how to build and deploy edge-based machine learning models that provide real-time alerts for distracted driving behaviors, while effectively collecting, processing, and analyzing footage to train these AI models.