Amazon Bedrock AgentCore enables us to deploy and operate highly capable AI agents securely, at scale. It offers infrastructure purpose-built for dynamic agent workloads, powerful tools to enhance agents, and essential controls for real-world deployment. In this talk, we'll dive deep into various aspects of how to implement AI Agent in Java using Spring AI including using MCP Streamable HTTP Client to talk to the MCP-compatible tools. We'll host our agent on Amazon Bedrock AgentCore and look at other AgentCore features like Observability (in standardized OpenTelemetry compatible format), Gateway (to securely connect to MCP-compatible tools) short and long-term Memory and Identity.

Amazon Bedrock AgentCore enables us to deploy and operate highly capable AI agents securely, at scale. It offers infrastructure purpose-built for dynamic agent workloads, powerful tools to enhance agents, and essential controls for real-world deployment. In this talk, we'll dive deep into various aspects of how to implement AI Agent in Java using Spring AI including using MCP Streamable HTTP Client to talk to the MCP-compatible tools. We'll host our agent on Amazon Bedrock AgentCore and look at other AgentCore features like Observability (in standardized OpenTelemetry compatible format), Gateway (to securely connect to MCP-compatible tools) short and long-term Memory and Identity.