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Course Outline
Introduction to Secure AI Agent Operations
- Addressing enterprise challenges in securing AI agents
- AgentCore’s security-centric design philosophy
- Overview of the identity, observability, and compliance modules
Identity and Access Management
- Configuring role-based access controls for agents
- Integrating federated identity with enterprise IAM systems
- Practical lab: Setting up secure identity and permission structures
Session Management and Security Controls
- Managing session-level state
- Mitigating risks of unauthorized persistence and data leakage
- Practical lab: Applying secure session policies
Observability for AI Agents
- Implementing structured logging and end-to-end traceability
- Utilizing metrics to monitor agent performance
- Practical lab: Connecting AgentCore to observability dashboards
Compliance and Auditability
- Key regulatory frameworks applicable to AI agents
- Maintaining audit logs and trace records
- Practical lab: Generating audit trails that meet compliance standards
Incident Response and Risk Mitigation
- Identifying and managing security incidents
- Setting up automated alerts and escalation procedures
- Practical lab: Simulating a compliance violation scenario
Best Practices and Enterprise Patterns
- Strategies for safe deployment in regulated sectors
- Designing governance frameworks for agent operations
- Emerging trends in AI agent compliance
Conclusion and Recommended Next Steps
Requirements
- In-depth knowledge of enterprise security architectures
- Practical experience with compliance standards (e.g., GDPR, HIPAA, SOC 2)
- Proficiency with observability platforms and AWS services
Target Audience
- Security Architects
- Compliance Officers
- Observability Engineers
14 Hours
