Course Outline

Introduction to AgentCore and Agentic AI

  • Agentic AI in the enterprise environment
  • Key components of AgentCore
  • Integration within the AWS Bedrock ecosystem

AgentCore Runtime and Gateway

  • Configuring the AgentCore Runtime for government use
  • Secure API integration with the Gateway
  • Practical exercise: deploying a sample agent for government applications

Memory and Stateful Agents

  • Implementing persistent context in stateful agents
  • Designing long-running workflows for continuous operations
  • Practical exercise: enabling session-based memory for enhanced user experience

Identity, Permissions, and Security

  • Role-based access control for AI agents in government systems
  • Federated identity management and enterprise integration
  • Practical exercise: configuring agent permissions to ensure secure operations

Observability and Monitoring

  • Logging and tracing capabilities with AgentCore for government
  • Metrics for usage and performance monitoring
  • Practical exercise: implementing observability dashboards for real-time insights

Scaling and Orchestrating Multi-Agent Systems

  • Design patterns for collaborative multi-agent systems
  • Performance optimization and reliability in government operations
  • Practical exercise: orchestrating specialized agents to enhance efficiency

Governance and Compliance

  • Ensuring auditability and safe deployment at scale for government projects
  • Compliance frameworks supported within AWS for government use
  • Best practices for regulated industries, including government agencies

Summary and Next Steps

Requirements

  • A comprehensive understanding of cloud-based artificial intelligence and machine learning services for government.
  • Practical experience with the AWS ecosystem tools.
  • Proficiency in enterprise security and observability concepts.

Audience

  • AI/ML engineers for government.
  • DevOps leads for government.
  • Solution architects for government.
 14 Hours

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