6 · Amazon AgentCore
The enterprise runtime for LangChain/LangGraph agents.
Amazon AgentCore is the enterprise runtime for AI agents built with LangChain/LangGraph. It adds memory, identity, tools, guardrails and observability at scale — the missing enterprise layer between your agents and Bedrock.
In simple terms
The managed enterprise runtime that makes LangChain agents production-ready on AWS.
How it works
- 1The LangGraph agent runs on the AgentCore Runtime.
- 2AgentCore Memory provides short-, long-term and semantic memory.
- 3AgentCore Identity controls who can access what (users, roles, OIDC/SSO).
- 4AgentCore Gateway gives secure access to tools and services via MCP.
- 5AgentCore Observability monitors and improves agents with traces, metrics and alerts.
Key points
- Enterprise-grade runtime with persistent memory and state.
- Secure, fine-grained permissions and policies.
- Scales on AWS infrastructure and integrates with Bedrock.
- Solves building auth, memory, tool security and monitoring from scratch.
Why it matters
AgentCore adds the enterprise capabilities — security, memory, tools, observability — that make LangChain agents production-ready on AWS without building them yourself.
Frequently asked questions
- What problem does AgentCore solve?
- It provides the enterprise plumbing (memory, identity, tools, guardrails, observability) so you don't build it from scratch.
- Does it work with LangGraph?
- Yes — it's designed to run LangChain/LangGraph agents in production.
More in Production AI Stack (2026)
1 · The Big Picture
The complete end-to-end production AI stack (2026).
2 · User Request Lifecycle
How one request flows through the whole system.
3 · LangChain Ecosystem
How LangChain, LangGraph, LangServe and LangSmith fit together.
4 · LangGraph Orchestration
Stateful, multi-step agent workflows.
5 · AWS Bedrock Integration
How LangChain talks to models through Amazon Bedrock.
7 · Memory & State Management
The four memory layers that make agents reliable.