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Duration 14 hours
Course Outline
AgentCore and Agentic AI Foundations
- The role of Agentic AI within enterprise environments
- Fundamental components of AgentCore
- Integration within the AWS Bedrock ecosystem
AgentCore Runtime and Gateway Mechanics
- Configuring the AgentCore Runtime environment
- Establishing secure API integrations via Gateway
- Practical exercise: Launching a representative agent instance
Memory Management and Stateful Agents
- Creating persistent contextual awareness
- Architecting workflows for long-duration agent operations
- Practical exercise: Activating session-based memory features
Identity, Access Control, and Security
- Implementing role-based access for AI agents
- Facilitating identity federation and enterprise system integration
- Practical exercise: Defining and applying agent permissions
Observability and System Monitoring
- Utilizing logging and tracing capabilities in AgentCore
- Tracking usage metrics and performance indicators
- Practical exercise: Building observability dashboards
Scaling and Orchestrating Multi-Agent Systems
- Effective design patterns for multi-agent collaboration
- Strategies for performance tuning and ensuring reliability
- Practical exercise: Coordinating specialized agent functions
Governance and Regulatory Compliance
- Ensuring auditability and secure large-scale rollouts
- Compliance frameworks available within the AWS ecosystem
- Recommended best practices for heavily regulated sectors
Conclusion and Future Recommendations
Requirements
- Familiarity with cloud-native AI/ML services
- Proficiency with AWS ecosystem tools
- Solid understanding of enterprise security and observability principles
Target Audience
- AI/ML Engineers
- DevOps Leaders
- Solution Architects
