Course Outline

Introduction to AgentCore and Agentic AI

  • Agentic AI in the enterprise
  • Core components of AgentCore
  • Positioning within AWS Bedrock ecosystem

AgentCore Runtime and Gateway

  • Setting up the AgentCore Runtime
  • Secure API integration with Gateway
  • Practical exercise: deploying a sample agent

Memory and Stateful Agents

  • Implementing persistent context
  • Designing long-running agent workflows
  • Practical exercise: enabling session-based memory

Identity, Permissions, and Security

  • Role-based access for AI agents
  • Identity federation and enterprise integration
  • Practical exercise: configuring agent permissions

Observability and Monitoring

  • Logging and tracing with AgentCore
  • Metrics for usage and performance
  • Practical exercise: implementing observability dashboards

Scaling and Orchestrating Multi-Agent Systems

  • Design patterns for multi-agent collaboration
  • Performance optimization and reliability
  • Practical exercise: orchestration of specialized agents

Governance and Compliance

  • Auditability and safe rollout at scale
  • Compliance frameworks supported in AWS
  • Best practices for regulated industries

Summary and Next Steps

Requirements

  • An understanding of cloud-based AI/ML services
  • Experience with AWS ecosystem tools
  • Knowledge of enterprise security and observability concepts

Audience

  • AI/ML engineers
  • DevOps leads
  • Solution architects
 14 Hours

Delivery Options

Private Group Training

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  • Customisation of the learning experience to achieve your goals -
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    • Practical hands-on exercises containing data / scenarios recognisable to the learners
  • Training scheduled on a date of your choice
  • Delivered online, onsite/classroom or hybrid by experts sharing real world experience

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