Deploy and Operate AI Agent with Amazon Bedrock AgentCore

Generative AI is redefining how users interact with applications by introducing adaptive, context-aware, and goal-oriented experiences. Amazon Bedrock AgentCore extends these capabilities by providing a managed runtime for deploying intelligent agents that can reason, remember, and act autonomously.

In this Cloud Lab, you will design and deploy a Cloud Labs Assistant, an intelligent agent powered by Amazon Bedrock AgentCore Runtime. This assistant will answer AWS-related questions, recommend learning labs tailored to user interests, and provide an interactive, chat-based learning experience. You’ll also explore how Bedrock AgentCore integrates with other AWS services to build, deploy, and operate intelligent agents. You will start by creating an Amazon ECR repository to store the container image that defines your agent’s runtime environment. Then, you’ll set up an Amazon S3 bucket to store Cloud Labs data, which the agent will use to recommend relevant learning paths and topics based on user queries.

After that, you’ll configure Bedrock AgentCore Memory to provide your agent with conversational persistence, allowing it to maintain session context and deliver personalized responses. Lastly, you’ll deploy your agent to the Bedrock AgentCore Runtime, enabling it to interact with users through a chatbot-like interface. After completing this Cloud Lab, you’ll have hands-on experience building and deploying an intelligent, generative AI-powered assistant using Amazon Bedrock AgentCore.

You’ll also understand how Bedrock AgentCore integrates reasoning, memory, and runtime management to deliver scalable, reliable, and context-aware AI applications.