Amazon Bedrock AgentCore streamlines AI agent development

Amazon Web Services (AWS) has announced new capabilities and tools to build AI agents. One key tool is Amazon Bedrock AgentCore, which will allow customers to deploy and operate highly capable AI agents securely at scale.

AgentCore is a set of services to deploy and operate AI agents using any framework and model. The challenge for AI adoption is building systems that can act autonomously across digital boundaries, while maintaining the security, reliability, and governance standards required for enterprise deployment. 

AgentCore helps developers bridge the critical gap between proof of concept and production for AI agents. It delivers composable solutions that allows organisations to move agents from prototypes to applications that can scale to millions of end-users. Customers like Innovaccer, Boomi, Epsilon, and Box are already building with AgentCore, AWS said.

Amazon Bedrock AgentCore services include:

AgentCore Runtime: Agents need a runtime that's both secure and dynamic enough to handle variable workloads. AgentCore Runtime supports interactive experiences with low latency and complex asynchronous workloads running up to eight hours, which AWS said is the longest in the industry. It is also the only framework-agnostic offering that provides complete session isolation.

AgentCore Memory: Just as humans rely on both short-term and long-term memory, agents rely on complex memory infrastructure to operate efficiently. AgentCore Memory makes it easy for developers to build context-aware agents by providing industry-leading long-term and short-term memory accuracy.

AgentCore Identity: Agents need to be able to securely access tools and resources to fulfill user requests using the right authentication, and AgentCore Identity provides seamless and secure agent authentication, integrating with existing identity providers such as Amazon Cognito, Microsoft Entra ID, and Okta.

AgentCore Gateway: AI agents need access to a wide range of tools to perform real world tasks, and AgentCore Gateway provides a secure way for agents to discover and use tools along with easy transformation of APIs, Lambda functions, and existing services into agent-compatible tools.

AgentCore Code Interpreter: AI agents need to write and execute code securely in sandbox environments to perform complex calculations, validate reasoning, process data, or generate visualisations. AgentCore Code Interpreter enables developers to customise environments with specific instance types and session properties to meet security requirements.

AgentCore Browser: The model-agnostic AgentCore Browser tool provides a fast, secure, cloud-based browser to enable AI agents to interact with websites at scale for tasks like form completion or navigating a website.

AgentCore Observability: Being able to track and trace every action of an agent is important for performance in production environments, and Amazon CloudWatch gives developers real-time visibility through built-in dashboards and telemetry for key metrics—while integrating with existing observability systems.

Source: AWS. Conceptual diagram describing Amazon Bedrock AgentCore.
Source: AWS. Conceptual diagram describing Amazon Bedrock AgentCore.

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