Course Overview
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.
Course Content
Module 1: Multi-Agent Architecture and Communications Patterns
- Single agent limitations and multi-agent benefits
- Instructor Demonstration: Building and Deploying Intelligent Financial Agents with Amazon Bedrock Strands and AgentCore - Task 1: Building a Personal Budget Assistant with Strands Agents
- Multi-agent communication patterns
- Memory and state management
- Instructor Demonstration: Building and Deploying Intelligent Financial Agents with Amazon Bedrock Strands and AgentCore - Task 2: Building a Multi-Agent System for Complex Financial Analysis
Module 2: Context Engineering and Performance Optimization
- Context as finite resource
- Context optimization techniques
- Tool design for context efficiency
Module 3: Security and Compliance Implementation
- Production Identity and Access Management
- VPC integration and network security
Module 4: Production Monitoring, Observability, and Evaluation
- Monitoring architecture
- AgentCore evaluation
- Enterprise observability integration
- Instructor Demonstration: Building and Deploying Intelligent Financial Agents with Amazon Bedrock Strands and AgentCore - Task 3: Deploying Production-Ready Agents with Amazon Bedrock AgentCore
Module 5: Well-Architected Agentic AI Systems
- Applying the Well-Architected framework
- Well-Architected deployment
- Production readiness
Module 6: Course Wrap-up
- Next steps and additional resources
- Course summary
Prerequisites
We recommend that attendees of this course have:
Course Objectives
In this course, learners will:
- 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.