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Duration 14 hours
Course Outline
Introduction to AgentCore and Agentic AI
- The role of agentic AI in enterprise environments
- Essential components of AgentCore
- Integration within the AWS Bedrock ecosystem
AgentCore Runtime and Gateway
- Initializing the AgentCore Runtime
- Establishing secure API integrations via Gateway
- Lab: Deploying a reference agent
Memory and Stateful Agents
- Creating persistent contextual awareness
- Developing workflows for long-running agent tasks
- Lab: Activating session-based memory features
Identity, Permissions, and Security
- Implementing role-based access control for AI agents
- Identity federation and enterprise system integration
- Lab: Configuring agent permission sets
Observability and Monitoring
- Utilizing logging and tracing features in AgentCore
- Tracking usage and performance metrics
- Lab: Building observability dashboards
Scaling and Orchestrating Multi-Agent Systems
- Design patterns for multi-agent collaboration
- Optimizing performance and ensuring reliability
- Lab: Orchestrating specialized agent functions
Governance and Compliance
- Ensuring auditability and safe large-scale rollouts
- Compliance frameworks available on AWS
- Best practices for heavily regulated sectors
Summary and Next Steps
Requirements
- Familiarity with cloud-based AI and ML services
- Practical experience with AWS ecosystem tools
- Understanding of enterprise security and observability principles
Target Audience
- AI/ML engineers
- DevOps leads
- Solution architects
