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Course Outline
Foundations of Secure Agent Operations
- Challenges enterprises face in securing AI agents
- AgentCore's security-first design principles
- Overview of identity, observability, and compliance modules
Identity and Access Management
- Implementing role-based access controls for agents
- Integrating federated identity with enterprise IAM systems
- Practical lab: Configuring secure identity and permissions
Session Management and Security Protocols
- Managing session-level state
- Mitigating unauthorized persistence and data leakage
- Practical lab: Enforcing secure session policies
Observability for AI Agents
- Implementing structured logging and traceability
- Utilizing metrics to monitor agent activity
- Practical lab: Integrating AgentCore with observability dashboards
Compliance and Audit Readiness
- Key compliance frameworks applicable to AI agents
- Maintaining audit logs and trace integrity
- Practical lab: Generating compliance-ready audit trails
Incident Response and Risk Management
- Detecting and addressing security incidents
- Setting up automated alerts and escalation workflows
- Practical lab: Simulating a compliance breach scenario
Best Practices and Enterprise Patterns
- Strategies for safe deployment in regulated environments
- Developing governance models for agent operations
- Emerging trends in AI agent compliance
Conclusion and Recommended Next Steps
Requirements
- Advanced knowledge of enterprise security models
- Experience with compliance frameworks (such as GDPR, HIPAA, SOC 2)
- Familiarity with observability platforms and AWS services
Intended Audience
- Security architects
- Compliance officers
- Observability engineers
14 Hours
