Building AgentOps with Amazon Bedrock AgentCore (1): Foundation and Gateway

As generative AI evolves into agentic AI that reasons and acts on its own, the challenge of managing complex tools, RAG, and orchestrators—beyond simple model responses—has emerged. At the production stage, the design of Harness Engineering surrounding the model—that is, the design of tools, memory, guardrails, and delegation paths—determines the final quality as much as the model's own performance does.

The methodology for reliably operating this is AgentOps. AgentOps manages the entire lifecycle of an agent, from build to governance, observation, evaluation, optimization, and redeployment. Since a 'failure' in agentic AI means not simply a wrong answer but 'wrong behavior,' building a robust Foundation capable of controlling this is essential.

The Foundation largely consists of the following elements:

• Orchestration Layer: Designing the internal behavioral architecture of the agent
• Core: A Gateway that unifies access to the model/agent/tool registry
• Runtime: The agent execution environment (serverless, containers, etc.)
• Data Layer: Data indexing and provision of short-term/long-term memory
• Common Layer: Operations, Security, and Observability

To implement this, AWS leverages Amazon Bedrock and Amazon Bedrock AgentCore. AgentCore containerizes and deploys agents built with various open-source frameworks, and provides the common layers needed for production operations—including memory, gateway, policy, identity, observability, and sandbox—as managed services.