In this course, you’ll learn about implementing production-ready multi-agent systems using Amazon Bedrock AgentCore, covering mulit-agent patterns, context optimization techniques, security configurations, and monitoring frameworks. You will examine the skills needed to move beyond proof-of-concept to scalable, secure, and observable agentic AI implementations. The course prepares you to design and deploy advanced agentic systems ready for real-world production environment

Learning Objectives

• Analyze scenarios that require multi-agent architectures.
• Describe primary multi-agent communication patterns and their use cases.
• Configure agent-as-tool patterns for production deployments.
• Implement memory sharing using available platform capabilities.
• Implement context management strategies for production workloads.
• Design context compression and optimization mechanisms.
• Optimize resource usage and cost management across multi-agent systems.
• Configure policy-based access control using AgentCore Policy Engine.
• Implement VPC integration for secure agent deployments.
• Implement distributed tracing and monitoring across multi-agent systems.
• Establish comprehensive agent evaluation frameworks.
• Configure integration patterns for enterprise observability systems
• Establish comprehensive audit trails and compliance monitoring.
• Integrate agentic systems with production APIs and services.
• Design deployment strategies for production environments.
• Assess production readiness and establish continuous improvement processes.

Prerequisites

We recommend that attendees of this course have:

• Agentic AI Foundations
• Building Agentic AI with Amazon Bedrock AgentCore