Spring AI SDK for Amazon Bedrock AgentCore is now Generally Available
New SDK automates complex infrastructure, letting Java devs build production AI agents with simple annotations.
Amazon has released the Spring AI SDK for Amazon Bedrock AgentCore to general availability, providing Java developers with a streamlined path to building and deploying production-scale AI agents. The SDK directly addresses the major hurdle in agentic AI: moving from proof-of-concept to scalable, governed, and secure systems. It integrates Amazon Bedrock AgentCore's platform capabilities—including managed runtime infrastructure, short- and long-term memory, browser automation, and sandboxed code execution—directly into the Spring framework using annotations and auto-configuration. This eliminates weeks of custom infrastructure coding required to fulfill the AgentCore Runtime contract, handle Server-Side Events (SSE) streaming, implement health checks, and manage rate limiting.
With the new SDK, developers can transform any Spring bean method into an AgentCore-compatible endpoint by simply adding the `@AgentCoreInvocation` annotation. The library automatically handles the complex runtime integration, including async task detection for proper scaling, backpressure handling for large responses, and connection lifecycle management. This allows teams to deploy agents to the fully managed, pay-per-use AgentCore Runtime for automatic scaling and cost efficiency, or run them on existing Amazon infrastructure. The design emphasizes convention over configuration, providing sensible defaults that align with AgentCore expectations, while maintaining deployment flexibility. The result is a significant reduction in the time and expertise required to operationalize autonomous AI systems that can plan and execute multi-step tasks.
- Automates AgentCore Runtime contract implementation, cutting weeks of infrastructure work to hours with simple `@AgentCoreInvocation` annotations.
- Provides built-in production capabilities like SSE streaming, health checks, rate limiting, and backpressure handling without custom code.
- Enables deployment to Amazon's pay-per-use AgentCore Runtime for auto-scaling or to existing infrastructure for maximum flexibility.
Why It Matters
Dramatically lowers the barrier for enterprises to deploy scalable, governed AI agents from concept to production, accelerating ROI.