Spring AI SDK for Amazon Bedrock AgentCore is now available

Agentic AI is transforming how organizations utilize generative AI, shifting from simple prompt-response interactions to autonomous systems capable of planning and executing complex multi-step tasks. While early proofs of concept in the Agentic AI space excite business stakeholders, scaling these concepts to production requires addressing challenges related to scalability, governance, and security. Amazon Bedrock AgentCore serves as a platform for building, deploying, and operating agents at scale using any framework and model.

Java developers are eager to create AI agents using familiar Spring patterns; however, production deployment necessitates complex infrastructure that is difficult to implement from scratch. Amazon Bedrock AgentCore provides building blocks such as managed runtime infrastructure (scalability, reliability, security, observability), as well as memory, browser automation, and sandboxed code execution. Integrating these capabilities into a Spring application currently involves writing custom controllers, handling Server-Side Events (SSE) streaming, implementing health checks, and managing rate limits.

With the new Spring AI AgentCore SDK, you can build production-ready AI agents and run them on the highly scalable AgentCore Runtime. This SDK is an open-source library that brings Amazon Bedrock AgentCore capabilities into Spring AI through familiar patterns: annotations, auto-configuration, and composable advisors. SpringAI Builders add a dependency, annotate a method, and the SDK takes care of the rest.

The AgentCore Runtime manages the agent lifecycle and scaling with a pay-per-use pricing model, meaning you don’t pay for idle compute. The runtime routes incoming requests to your agent and monitors its health, but this requires your agent to adhere to a contract. The contract stipulates that the implementation exposes two endpoints: /invocations to receive requests and return responses in either JSON or SSE streaming, and /ping for health checks.

The SDK implements this contract automatically, including async task detection that reports busy status when your agent is processing. Beyond the contract, the SDK provides additional capabilities for production workloads such as handling SSE responses with proper framing and managing connection lifecycles for large responses. It also includes rate limiting to protect your agent from traffic spikes and limit per-user consumption. You focus on agent logic while the SDK manages runtime integration.