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Course Outline
Introduction to AgentCore and Agentic AI
- Agentic AI in the enterprise context.
- Core components of AgentCore.
- Positioning within the AWS Bedrock ecosystem.
AgentCore Runtime and Gateway
- Setting up the AgentCore Runtime.
- Secure API integration via 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 control 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 evaluation.
- Practical exercise: implementing observability dashboards.
Scaling and Orchestrating Multi-Agent Systems
- Design patterns for multi-agent collaboration.
- Performance optimization and reliability strategies.
- Practical exercise: orchestrating specialized agents.
Governance and Compliance
- Auditability and safe rollout at scale.
- Compliance frameworks supported within AWS.
- Best practices for regulated industries.
Summary and Next Steps
Requirements
- A solid understanding of cloud-based AI/ML services.
- Practical experience with AWS ecosystem tools.
- Familiarity with enterprise security and observability concepts.
Target Audience
- AI/ML engineers.
- DevOps leads.
- Solution architects.
14 Hours
