AgentsSeptember 3, 2026via AWS Machine Learning Blog
Migrate agentic workloads to Amazon Bedrock AgentCore
Why it matters
Amazon is lowering the operational bar to move agents from dev to production, addressing the gap between proof-of-concept and deployed autonomy. This is agent infrastructure maturing.
Key signals
- Migration targets: LangGraph → Bedrock AgentCore Runtime, Gateway, Memory, then Strands Agents model-driven planning
- Two-stage deployment approach reduces operational burden
- Focus on production reliability (not notebook prototyping)
- AWS Bedrock AgentCore as centralized agent platform
- Two-stage migration pattern: Runtime/Gateway/Memory → model-driven planning on Strands Agents
- LangGraph customer support agent used as reference implementation
- Focus on retiring operational burdens in agent deployment
- AWS framing agents as a production category requiring specialized infrastructure
The hook
Not a pilot. Amazon Bedrock AgentCore lets you move agentic workloads from notebook to production — with a migration blueprint.
An agent that works in a notebook is not an agent in production. This post walks through migrating a LangGraph customer support agent to Amazon Bedrock AgentCore in two stages: onto Runtime, Gateway, and Memory, then to model-driven planning on Strands Agents, retiring operational burdens along the …