Notes from production

Blog

Practical articles on AWS Bedrock cost optimization, knowledge graphs, AI infrastructure, and cloud architecture — from the ThinkXL team.

AWS Production Readiness Checklist for AI Workloads

An AI workload on AWS is ready for production when every check below is backed by evidence you can point to: a configuration, an alarm, a test result, a restore record. The checklist has 44 checks acr

LLM Inference on AWS: Every Option Explained

AWS gives you two fundamentally different ways to run an LLM -SageMaker, you provision and pay for the infrastructure that serves the model. Bedrock, AWS already runs the model, and you just call

How to Build RAG on Your S3 Documents with Bedrock

If your documents already sit in Amazon S3 and you want to ask questions of them, the shortest path on AWS is Amazon Bedrock Managed Knowledge Base: point it at the bucket, and it handles parsing,

S3 Vectors vs OpenSearch Serverless for RAG on AWS

This is a choice you only face on the customer-managed path — if you have not ruled out the fully managed option yet, [building RAG on your S3 documents with Bedrock](/blog/rag-on-s3-documents-with-be

What an AI Agent Costs Per Conversation on AgentCore

You can read AgentCore's per-service rates straight off the AWS pricing page. What that page can't tell you — and what you actually need before you build a business on agents — is what one of your u

When Is Self-Hosting an LLM Cheaper Than Bedrock?

Two questions send teams down this path: "our Bedrock bill is growing, should we run this on our own GPU?" and "we fine-tuned a Llama, where does it go?" For most teams the answer to both is no, a