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Duration 14 hours
Course Outline
Introduction to AgentCore and Agentic AI
- The role of Agentic AI in enterprise environments
- Key architectural components of AgentCore
- Contextual positioning within the AWS Bedrock ecosystem
AgentCore Runtime and Gateway
- Initial configuration of the AgentCore Runtime
- Secure API integration utilizing Gateway
- Hands-on exercise: Deploying a sample agent
Memory and Stateful Agents
- Establishing persistent context
- Architecting workflows for long-running agents
- Hands-on exercise: Configuring session-based memory
Identity, Permissions, and Security
- Implementing role-based access for AI agents
- Identity federation and enterprise integration strategies
- Hands-on exercise: Configuring agent permissions
Observability and Monitoring
- Logging and tracing capabilities in AgentCore
- Tracking metrics for usage and performance
- Hands-on exercise: Setting up observability dashboards
Scaling and Orchestrating Multi-Agent Systems
- Design patterns for multi-agent collaboration
- Strategies for performance optimization and reliability
- Hands-on exercise: Orchestrating specialized agents
Governance and Compliance
- Ensuring auditability and safe large-scale rollouts
- Compliance frameworks supported within AWS
- Best practices for highly regulated industries
Conclusion and Recommended Next Steps
Requirements
- Familiarity with cloud-based AI and ML services
- Practical experience with AWS ecosystem tools
- Solid understanding of enterprise security and observability principles
Target Audience
- AI and ML engineers
- DevOps leaders
- Solution architects
