You’ve built a LangGraph agent that works fine on your laptop. The next challenge is getting it running in a scalable, serverless production infrastructure without having to redesign the whole thing.

That’s where AWS Bedrock AgentCore comes in. In this guide, I’ll show you how to put a wrapper for your existing agent to make it run on AgentCore, set up an AgentCore project, test it locally, deploy it to AWS, and invoke it after deployment.

What Is AWS Bedrock AgentCore?

AgentCore is a serverless hosting platform designed by AWS to deploy, scale, and operate your AI agents securely without you managing the infrastructure. It works with any open-source framework like LangGraph, Strands, CrewAI, or LlamaIndex and supports Large Language Models like OpenAI's GPT, Google's Gemini, or Anthropic's Claude. So you don’t have to rewrite the agent logic. It also provides session isolation, persistent memory, observability and identity management.

The deployment is managed through the AgentCore CLI, a Node.js tool that scaffolds projects, runs a local dev server, and deploys to AWS using CDK under the hood.