Building Agentic AI with Amazon Bedrock AgentCore

This course is intended for:

- Software developers seeking intermediate knowledge for building agentic systems

- Technical professionals exploring AI capabilities and interested in building agentic AI systems.

- Development teams building agentic AI solutions.

In this course, you will learn to:

• Define agentic AI characteristics and differentiate them from traditional AI systems.
• Identify the core agent components and their interactions.
• Describe how Bedrock AgentCore services support agentic AI.
• Deploy agents by using supported frameworks with AgentCore Runtime.
• Describe the core features of AgentCore Runtime.
• Configure serverless execution with session isolation.
• Configure AgentCore Identity for enterprise security requirements.
• Create policies to secure agent tool calls using AgentCore Policy.
• Implement secure token management and permission delegation.
• Ensure compliance with data governance and audit requirements.
• Implement different tool integration patterns, including built-in tools and protocol-based tools.
• Design and deploy Model Context Protocol (MCP) servers and clients for extensible agent capabilities.
• Describe common authentication patterns for agent tool use.
• Configure AgentCore Gateway components for secure and authorized tool access.
• Implement agentic memory patterns for different use cases.
• Configure AgentCore Memory operations for context-aware development.
• Optimize memory performance for production workloads.
• Configure AgentCore Observability for production monitoring.
• Implement Amazon CloudWatch integration and specialized tracing.
• Describe the core features of AgentCore Evaluations.
• Integrate agentic systems with production APIs and services.
• Design deployment strategies for production environments.
• Assess production readiness and establish continuous improvement processes

Day 1:

Module 1: Foundations of Agentic AI Patterns

• Agent building blocks
• Amazon Bedrock AgentCore introduction

Module 2: AgentCore Runtime and Framework Integration

• Supported frameworks and implementation
• AgentCore Runtime overview
• Infrastructure and deployment

Module 3: Security and Identity Management

• Security and identity management
• Securing your agents with AgentCore Identity

Module 4: Tool Integration and AgentCore Gateway

• Amazon Bedrock AgentCore Policy
• Built-in tools and custom integration
• Model Context Protocol (MCP)
• AgentCore Gateway
• Implementing AgentCore Gateway
• Amazon Bedrock AgentCore Policy

Module 5: Agentic Memory Implementation

• Agentic memory core concepts
• AgentCore Memory
• Securing AgentCore Memory
• Hands-on Lab: Enhance and Scale Agents with Amazon Bedrock AgentCore

Module 6: Production Monitoring and Observability 

• Monitoring agents with AgentCore Observability
• Verifying agent performance with AgentCore Evaluation

Module 7: Course Wrap-up

• Next steps and additional resources
• Course summary

We recommend that attendees of this course have:

• Agentic AI Foundations

• GK910031 - Agentic AI Foundations

None

• GK1979 - DevOps Engineering on AWS
• GK910029 - Machine Learning Engineering on AWS

Activities:

This course includes presentations, hands-on lab, and group exercises.