Training AWS

Training goals

code: AWS-BAASA | version: 1.0.0

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 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.

 

Intended audience

  • Software developers seeking intermediate knowledge for building advanced agentic AI systems
  • Technical professionals exploring AI capabilities and interested in building advanced agentic AI systems.
  • Development teams building advanced agentic AI solutions.

Conspect Show list

  • 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
    • Instructor Demonstration: Building and Deploying Intelligent Financial Agents with Amazon Bedrock Strands and AgentCore
  • 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
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Additional information

Prerequisites

We recommend that attendees of this course have:

  • Agentic AI Foundations
  • Building Agentic AI with Amazon Bedrock AgentCore
Difficulty level
Duration 1 day
Certificate

The participants will obtain certificates signed by AWS (course completion).
Trainer

AWS Authorized Instructor (AAI)

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